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Bozios, Athanasios. "Fog Computing : Architecture and Security aspects." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-80178.
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As the number of Internet of Things (IoT) devices that are used daily is increasing, the inadequacy of cloud computing to provide neseccary IoT-related features, such as low latency, geographic distribution and location awareness, is becoming more evident. Fog computing is introduced as a new computing paradigm, in order to solve this problem by extending the cloud‟s storage and computing resources to the network edge. However, the introduction of this new paradigm is also confronted by various security threats and challenges since the security practices that are implemented in cloud computing cannot be applied directly to this new architecture paradigm. To this end, various papers have been published in the context of fog computing security, in an effort to establish the best security practices towards the standardization of fog computing. In this thesis, we perform a systematic literature review of current research in order to provide with a classification of the various security threats and challenges in fog computing. Furthermore, we present the solutions that have been proposed so far and which security challenge do they address. Finally, we attempt to distinguish common aspects between the various proposals, evaluate current research on the subject and suggest directions for future research.
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Rahafrouz, Amir. "Distributed Orchestration Framework for Fog Computing." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-77118.
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The rise of IoT-based system is making an impact on our daily lives and environment. Fog Computing is a paradigm to utilize IoT data and process them at the first hop of access network instead of distant clouds, and it is going to bring promising applications for us. A mature framework for fog computing still lacks until today. In this study, we propose an approach for monitoring fog nodes in a distributed system using the FogFlow framework. We extend the functionality of FogFlow by adding the monitoring capability of Docker containers using cAdvisor. We use Prometheus for collecting distributed data and aggregate them. The monitoring data of the entire distributed system of fog nodes is accessed via an API from Prometheus. Furthermore, the monitoring data is used to perform the ranking of fog nodes to choose the place to place the serverless functions (Fog Function). The ranking mechanism uses Analytical Hierarchy Processes (AHP) to place the fog function according to resource utilization and saturation of fog nodes’ hardware. Finally, an experiment test-bed is set up with an image-processing application to detect faces. The effect of our ranking approach on the Quality of Service is measured and compared to the current FogFlow.
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Grandi, Stefano. "Sviluppo di Servizi Android per applicazioni Fog Computing." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017.
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Il Cloud Computing è stata la risposta alla crescente domanda di capacità di calcolo, di memorizzazione di dati e di flessibilità nel loro approvvigionamento. Ma se da un lato il Cloud ha permesso di sopperire alle limitazioni hardware a cui i dispositivi utente sono sottoposti, questo nuovo paradigma soffre inevitabilmente di quelle che sono le latenze dovute allo scambio di informazioni attraverso Internet.
Inoltre la rete Internet, già messa a dura prova dal continuo e crescente traffico dati, non ha beneficiato dell'utilizzo del paradigma Cloud e teme quello che si appresta a diventare di vastissimo ambito di utilizzo, il paradigma dell'Internet of Things (IoT), per il quale si intende una famiglia di tecnologie il cui scopo è rendere qualunque tipo di oggetto, un dispositivo collegato ad Internet.
È proprio in questo scenario che nasce il paradigma del Fog Computing, cioè l'idea di costruire la stessa architettura del Cloud, fisicamente più vicina ai client che, a causa delle loro scarse capacità di elaborazione, memoria o autonomia energetica, necessitano di demandare al Cloud l'esecuzione di operazioni costose.
Il Fog si pone quindi l'obiettivo di ridurre al minimo la latenza nelle comunicazioni tra i client e i nodi Fog (dispositivi fisici che si occupano dell'esecuzione delle richieste di servizi), permettendo ai client, di non sottostare più agli svantaggi dovuti alla comunicazione Internet che si hanno con il Cloud, e scaricando quindi la rete Internet di traffico in eccesso.
Il progetto di tesi ha quindi visto lo sviluppo di una applicazione Android, chiamata Fog Network Application, in grado di creare e gestire una Fog Network, cioè una rete virtuale, interna alla rete locale LAN, alla quale tutti i dispositivi in possesso dell'applicazione siano in grado di connettersi, quindi fornire dei servizi generici e/o tramite la definizione di una interfaccia, e infine richiedere l'utilizzo di tali servizi.
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Valieri, Mario. "Dynamic Resource and Service Discovery in Fog Computing." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22265/.
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The cloud computing is already a well-known paradigm, known and used in both business and consumers areas. It provides a lot of advantages, but today the necessity of data security and low latency is rapidly increasing. Nowadays, in next generation networks (NGN), the fog computing paradigm is able to satisfy strict latency and security requirements using distributed computational power. In a dynamic fog orchestration scenario, the discovery of available resources and services is a fundamental aspect to achieve a good quality system.
This thesis is focused on the study and comparison of service and node discovery techniques and protocols, with the aim of finding an optimal solution to the problem related to a preexisting fog service orchestration system. Once the optimal solution is detected, a working implementation is proposed and evaluated with appropriate experimental measurements, particularly relevant for network administration.
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Machado, Miguel Chagas Bilhau. "Monitoring system based on fog computing." Master's thesis, Universidade de Aveiro, 2017. http://hdl.handle.net/10773/23462.
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Mestrado em Engenharia de Computadores e TelemáticaThis thesis is a contribution of an architectural solution, describing a system that represents an extra layer of computing power, placed between the cloud and sensor networks, acting both as a mediator whose central task is to manage, monitor and collect data from geographically-located groups of sensor nodes and as a communication hub to the cloud with which data is exchanged in a compact and minimalist fashion. The latter is accomplished by designing nodes as autonomous entities, able to organise themselves in smaller groups, within the system. Additionally, these entities possess inherent mechanisms which aim to accomplish fault tolerance within groups of nodes, maintaining the status quo of the overall system while performing in an ubiquitous environment, continuously embracing contextual changes. The overall solution was tested in a proof of concept where we conceived three test cases that helped us validate it.
Este documento apresenta uma arquitectura como solução para o desenvolvimento de uma camada extra de poder computacional entre os serviços na núvem e a Internet das Coisas, denominada de computação no nevoeiro. Esta camada é responsável pela gestão e recolha de dados provenientes de conjuntos de sensores, geograficamente distribuídos, em níveis inferiores. Assim, o nevoeiro permite servir como ponto de agregação comunicando directamente com a núvem, minimizando a quantidade de tráfego na rede. A solução descreve a camada de nevoeiro como um conjunto de grupos de nós que se agrupam e organizam como um todo, autonomamente. Existem ainda mecanismos auxiliares que permitem a existência de um certo grau de tolerância a falhas de forma a manter o status quo do sistema em ambientes ubíquos, lidando com as constantes alterações de contexto. A solução foi testada e validada através de uma prova de conceito onde foram realizados três casos de teste, concebidos de forma a abranger todos os componentes da mesma.
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Mebrek, Adila. "Fog Computing pour l’Internet des objets." Thesis, Troyes, 2020. http://www.theses.fr/2020TROY0028.
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Le Fog Computing constitue une approche prometteuse dans le contexte de l’Internet des Objets (IoT) car il fournit des fonctionnalités et des ressources à l’extrémité du réseau, plus près des utilisateurs finaux. Cette thèse étudie les performances du Fog Computing dans le cadre des applications IoT sensibles à la latence. La première problématique traitée concerne la modélisation mathématique d’un système IoT-fog-cloud, ainsi que les métriques de performances du système en termes d’énergie consommée et de latence. Cette modélisation nous permettra par la suite de proposer diverses stratégies efficaces de distribution de contenu et d’allocation des ressources dans le fog et le cloud. La deuxième problématique abordée dans cette thèse concerne la distribution de contenu et de données des objets dans des systèmes fog/cloud. Afin d’optimiser simultanément les décisions d’offloading et d’allocation des ressources du système, nous distinguons entre deux types d’applications IoT : (1) applications IoT à contenu statique ou avec des mises à jour peu fréquentes ; et (2) applications IoT à contenu dynamique. Pour chaque type d’application, nous étudions le problème d’offloading de requêtes IoT dans le fog. Nous nous concentrons sur les problèmes d'équilibrage de charge afin de minimiser la latence et l’énergie totale consommée par le systèmeFog computing is a promising approach in the context of the Internet of Things (IoT) as it provides functionality and resources at the edge of the network, closer to end users. This thesis studies the performance of fog computing in the context of latency sensitive IoT applications. The first issue addressed is the mathematical modeling of an IoT-fogcloud system, and the performance metrics of the system in terms of energy consumed and latency. This modeling will then allow us to propose various effective strategies for content distribution and resource allocation in the fog and the cloud. The second issue addressed in this thesis concerns the distribution of content and object data in fog / cloud systems. In order to simultaneously optimize offloading and system resource allocation decisions, we distinguish between two types of IoT applications: (1) IoT applications with static content or with infrequent updates; and (2) IoT applications with dynamic content. For each type of application, we study the problem of offloading IoT requests in the fog. We focus on load balancing issues to minimize latency and the total power consumed by the system
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Huang, Chih-Kai. "Scalability of public geo-distributed fog computing federations." Electronic Thesis or Diss., Université de Rennes (2023-....), 2024. http://www.theses.fr/2024URENS055.
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Construire une plateforme de fog computing publique, géo-distribuée, multi-tenant et à grande échelle, où n'importe quelle application peut être déployée, nécessite un grand nombre de ressources de calcul placées à différents endroits stratégiques couvrant un pays entier ou même un continent. L'un des défis pour réaliser cette plateforme publique de fog est la scalabilité. À cette fin, cette thèse se concentre sur la résolution de certains défis liés à l'évolutivité et propose une série de solutions. Tout d'abord, nous présentons le concept de méta-fédérations, où de nombreux fournisseurs de ressources locaux indépendants peuvent louer leurs ressources à plusieurs fournisseurs de fog afin de résoudre les problèmes de couverture de service et d'utilisation des ressources. Nous proposons UnBound, un système scalable de meta-federations qui aborde spécifiquement les défis difficiles du multi-tenancy introduits par les méta-fédérations. Ensuite, nous proposons deux systèmes de surveillance conçus pour les environnements de fédération de clusters géo-distribués, Acala et AdapPF, qui visent à réduire le trafic réseau inter-cluster de la surveillance tout en maintenant la précision des données de surveillanceBuilding a large-scale, multi-tenant, public, geo-distributed fog computing platform where any application can be deployed requires a large number of computing resources placed at different strategic locations spanning an entire country or even a continent. One of the challenges to realizing this public fog platform is scalability. To this end, this thesis focuses on addressing some scalability challenges and proposes a series of solutions. First, we present the meta-federations concept, where many independent local resource providers may lease their resources to multiple fog providers to solve the service coverage and resource utilization issues. We propose UnBound, a scalable meta-federations framework that specifically addresses the difficult multi-tenancy challenges introduced by meta-federations. Second, we propose two monitoring frameworks designed for geo-distributed cluster federation environments, Acala and AdapPF, which aim to reduce the cross-cluster network traffic of monitoring while maintaining the accuracy of the monitoring data
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Butterfield, Ellis H. "Fog Computing with Go: A Comparative Study." Scholarship @ Claremont, 2016. http://scholarship.claremont.edu/cmc_theses/1348.
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The Internet of Things is a recent computing paradigm, de- fined by networks of highly connected things – sensors, actuators and smart objects – communicating across networks of homes, buildings, vehicles, and even people. The Internet of Things brings with it a host of new problems, from managing security on constrained devices to processing never before seen amounts of data. While cloud computing might be able to keep up with current data processing and computational demands, it is unclear whether it can be extended to the requirements brought forth by Internet of Things.
Fog computing provides an architectural solution to address some of these problems by providing a layer of intermediary nodes within what is called an edge network, separating the local object networks and the Cloud. These edge nodes provide interoperability, real-time interaction, routing, and, if necessary, computational delegation to the Cloud.
This paper attempts to evaluate Go, a distributed systems language developed by Google, in the context of requirements set forth by Fog computing. Similar methodologies of previous literature are simulated and benchmarked against in order to assess the viability of Go in the edge nodes of Fog computing architecture.
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Struhar, Vaclav. "Improving Soft Real-time Performance of Fog Computing." Licentiate thesis, Mälardalens högskola, Inbyggda system, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-55679.
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Fog computing is a distributed computing paradigm that brings data processing from remote cloud data centers into the vicinity of the edge of the network. The computation is performed closer to the source of the data, and thus it decreases the time unpredictability of cloud computing that stems from (i) the computation in shared multi-tenant remote data centers, and (ii) long distance data transfers between the source of the data and the data centers. The computation in fog computing provides fast response times and enables latency sensitive applications. However, industrial systems require time-bounded response times, also denoted as RT. The correctness of such systems depends not only on the logical results of the computations but also on the physical time instant at which these results are produced. Time-bounded responses in fog computing are attributed to two main aspects: computation and communication. In this thesis, we explore both aspects targeting soft RT applications in fog computing in which the usefulness of the produced computational results degrades with real-time requirements violations. With regards to the computation, we provide a systematic literature survey on a novel lightweight RT container-based virtualization that ensures spatial and temporal isolation of co-located applications. Subsequently, we utilize a mechanism enabling RT container-based virtualization and propose a solution for orchestrating RT containers in a distributed environment. Concerning the communication aspect, we propose a solution for a dynamic bandwidth distribution in virtualized networks.
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Civolani, Lorenzo. "Fast Docker Container Deployment in Fog Computing infrastructures." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/17701/.
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I contenitori software, meglio noti come container, realizzano ambienti virtuali in cui molteplici applicazioni possono eseguire senza il rischio di interferire fra di loro.
L'efficienza e la semplicità dell'approccio hanno contribuito al forte incremento della popolarità dei contaier, e, tra le varie implementazioni disponibili, Docker è di gran lunga quella più diffusa.
Sfortunatamente, a causa delle loro grandi dimensioni, il processo di deployment di un container da un registro remoto verso una macchina in locale tende a richiedere tempi lunghi.
La lentezza di questa operazione è particolarmente svantaggiosa in un'architettura Fog computing, dove i servizi devono muoversi da un nodo all'altro in risposta alla mobilità degli utenti.
Tra l'altro, l'impiego di server a basse prestazioni tipico di tale paradigma rischia di aggravare ulteriormente i ritardi.
Questa tesi presenta FogDocker, un sistema che propone un approccio originale all'operazione di download delle immagini Docker con l'obiettivo di ridurre il tempo necessario per avviare un container.
L'idea centrale del lavoro è di scaricare soltanto il contenuto essenziale per l'esecuzione del container e procedere immediatamente con l'avvio; poi, in un secondo momento, mentre l'applicazione è già al lavoro, il sistema può proseguire col recupero della restante parte dell'immagine.
I risultati sperimentali confermano come FogDocker sia in grado di raggiungere una riduzione notevole del tempo necessario per avviare un container.
Tale ottimizzazione si rivela essere particolarmente marcata quando applicata in un contesto a risorse computazionali limitate.
I risultati ottenuti dal nostro sistema promettono di agevolare l'adozione dei software container nelle architetture di Fog computing, dove la rapidità di deployment è un fattore di vitale importanza.
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Meskine, Mohamed. "Vehicular Fog/Edge Computing to improve dependability and performance." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.
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We have more and more objects connected to the network. These objects need local information increasingly. This means that cloud computing is not suitable in some applications. This is also due to the high latency that it presents.
The thesis is focused on the vehicular field. In the presented appli- cation, we will use fog computing and 5G. These two technologies are important to guarantee a good performance. This is important because thanks to that we can avoid an accident.
The application is to provide that the user will be able to see the vehicles within a radius of 100 meters. The vehicles within this radius will be presented on the display inside the vehicle. Inside the vehicle there will be a processor that sends messages to the driver in case of emergency. In case that the warning remains, there will be automatic braking and/or steering.
The idea of the thesis is to improve three aspects: latency, mobility and reliability. Latency has been improved thanks to the idea of uncorrelation. Mobility, i.e. the time it takes to pass control from one small cell to another, has been improved thanks to the interconnection between the fog nodes and the information on the user’s destination. Reliability is improved thanks to the interconnection between layers and besides thanks to the use of two links.
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Fahs, Ali Jawad. "Proximity-aware replicas management in geo-distributed fog computing platforms." Thesis, Rennes 1, 2020. http://www.theses.fr/2020REN1S076.
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L'architecture géo-distribuée de fog computing fournit aux utilisateurs des ressources accessibles avec une faible latence. Cependant, exploiter pleinement cette architecture nécessite une distribution similaire de l'application par l'utilisation de techniques de réplication. Par conséquent, la gestion de ces répliques doit intégrer des algorithmes prenant en compte la proximité aux différents niveaux de gestion des ressources du système. Dans cette thèse, nous avons abordé ce problème à travers trois contributions. Premièrement, nous avons conçu un système de routage des requêtes entre les utilisateurs et les ressource prenant en compte la proximité. Deuxièmement, nous avons proposé des algorithmes dynamiques pour le placement des répliques prenant en compte les derniers percentiles de la latence. Enfin, nous avons développé un système de mise à l’échelle automatique qui ajustent le nombre des répliques de l'application en fonction de la charge subie par les applications fog computingGeo-distributed fog computing architectures provide users with resources reachable within low latency. However, fully exploiting the fog architecture requires a similar distribution of the application by the means of replication. As a result, fog application replica management should implement proximity-aware algorithms to handle different levels of resource management. In this thesis, we addressed this problem over three contributions. First, we designed a proximity-aware user-to-replica routing mechanism. Second, we proposed dynamic tail-latency-aware replica placement algorithms. Finally, we developed autoscaling algorithms to dynamically scale the application resources according to the non-stationary workload experienced by fog platforms
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Khan, Kafeel Ahmed. "Web-based Management of Fog Computing Services implemented in Docker." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18934/.
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The aim and motivation of this thesis project is to introduce the implementation of the Fog computing scenario. For possible demonstration, we use the feasible or concur solution already deployed in the cloud computing paradigm. An emerging trend of IoT in the current era required more development in cloud computing due to the centralized control of resources that is no-more beneficial in the IoT base scenario. A distributed base approach called Fog computing is introduced that manages the services without being the use of a centralized pool of cloud. Although, Fog cannot fully function without being centralized control. But in order to implement the Fog node, I used a hypervisor supported device to configure virtual machines on the server and considered it as edge or fog node and make it capable to hold Fog services. Further, I used the docker container orchestration tool configure along with the Apache server that can host webpages to interact with the Docker API support and last a local machine that is used to access the fog node by a browser. Further, I analyze the response time of on-demand service with respect to the number of containers and conclude that using Fog as an intermittent node reduces the overall container formation time as compared to those users that directly connect with the cloud server this approach can fulfill some level of latency requirement by IoT devices.
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Bhal, Siddharth. "Fog computing for robotics system with adaptive task allocation." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78723.
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The evolution of cloud computing has finally started to affect robotics.
Indeed, there have been several real-time cloud applications making their way into robotics as of late. Inherent benefits of cloud robotics include providing virtually infinite
computational power and enabling collaboration of a multitude of connected devices.
However, its drawbacks include higher latency and overall higher energy consumption.
Moreover, local devices in proximity incur higher latency when communicating among themselves via the cloud. At the same time, the cloud is a single point of failure in the network. Fog Computing is an extension of the cloud computing paradigm providing data, compute, storage and application services to end-users on a so-called edge layer. Distinguishing characteristics are its support for mobility and dense geographical distribution. We propose to study the implications of applying fog computing concepts in robotics by developing a middle-ware solution for Robotic Fog Computing Cluster solution for enabling adaptive distributed computation in heterogeneous multi-robot systems interacting with the Internet of Things (IoT). The developed middle-ware has a modular plug-in architecture based on micro-services and facilitates communication of IOT devices with the multi-robot systems.
In addition, the developed middle-ware solutions support different load balancing or task allocation algorithms. In particular, we establish that we can enhance the performance of distributed system by decreasing overall system latency by using already established multi-criteria decision-making algorithms like TOPSIS and TODIM with naive Q-learning and with Neural Network based Q-learning.Master of Science
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POLTRONIERI, Filippo. "Value-of-Information Middlewares for Fog and Edge Computing." Doctoral thesis, Università degli studi di Ferrara, 2021. http://hdl.handle.net/11392/2488252.
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Fog and Edge Computing aim to deliver low-latency, immersive, and powerful services by processing information close to both devices and users. This is well suited for IoT applications in Smart City, where IoT gateways, Cloudlets, Base Stations, and other computational nodes can process (part of) the data generated by the multitude of IoT sensors directly at the edge of the network. However, the implementation of Fog and Edge Computing is challenging because it requires to deal with a (limited number of) constrained devices, dynamic services' requirements, and heterogeneous network conditions. Differently from the Cloud, where computational resources are supposed to be unlimited, Fog and Edge services should be capable to adapt to scarce and constrained resources and deal with the deluge of IoT data. To facilitate the adoption of Fog and Edge Computing this thesis proposes innovative middlewares capable of providing comprehensive solutions to address the highly dynamic characteristics of these environments. These middlewares provide functions to allocate and distribute Fog and Edge services among the available computational devices, monitor the status of the environment, and promptly modify their configuration.
To deal with the IoT data deluge this thesis investigates the interesting criterion of Value-of-Information (VoI). Originally born as an extension of Shannon's Information Theory for decision making science, researchers have studied VoI as an information management tool to select and prioritize information processing and dissemination. For this purpose, this thesis proposes the adoption of information management policies allowing the definition of service components, composable software modules that can be chained to create larger and more complex services. In addition, the middlewares presented in this thesis leverage the promising concept of VoI to select only the most valuable piece of information for processing and dissemination and to scale computational workload in an automated and lossiness fashion. This would enable to reduce the computational and network load and to propose innovative methodologies to optimize the available resources.
The research efforts presented in this thesis are the results of the collaboration with international institutes and a research period at the Florida Institute for Human and Machine Cognition (IHMC), FL, USA.Con i termini Fog ed Edge Computing si indicano dei paradigmi computazionali che, spostando l'elaborazione dei dati IoT nelle prossimità sia dei dispositivi che degli utenti, mirano a fornire servizi a bassa latenza, immersivi e real-time. Fog ed Edge Computing trovano applicazione in contesti Smart Cities, dove è possibile sfruttare la capacità computazionale di gateway IoT, Cloudlet e Base Station per elaborare parte dei dati generati dall'IoT direttamente ai margini della rete. L'adozione dei paradigmi di Fog ed Edge Computing è tuttavia complessa in quanto pone una serie di sfide tra cui il processamento dell’enorme mole di dati generati dall’IoT, la presenza di un numero limitato di dispositivi altamente eterogenei e con capacità computazionali scarse, requisiti di servizio altamente dinamici e reti con caratteristiche eterogenee. Per garantire i requisiti stringenti di bassa latenza, soluzioni per Fog ed Edge Computing devono essere in grado di utilizzare al meglio le scarse risorse a disposizione, gestendole al meglio. Se questi paradigmi sono oggetto di ampie ricerche, vi è la necessità di investigare soluzioni innovative che consentano di gestire l’enorme mole dati IoT e permettere una concreta applicazione di Fog ed Edge Computing. Questa tesi propone middleware innovativi in grado di fornire soluzioni complete per fronteggiare al meglio le caratteristiche altamente dinamiche di scenari Smart Cities, fornendo metodologie e strumenti per allocare e distribuire servizi tra le risorse a disposizione, monitorare lo stato delle risorse e modificare prontamente la loro configurazione. Come criterio innovativo per la prioritizzazione dei dati IoT per processamento e disseminazione, questa tesi adotta il concetto di Value-of-Information (VoI), nato come estensione della Teoria dell'Informazione di Shannon e applicato in ambiti decisionali. A tal fine, questa tesi propone politiche di gestione delle informazioni che consentono di realizzare servizi modulari e facilmente (ri-)componibili e tecniche di ottimizzazione innovative che ben si adattano a questi servizi. Inoltre, i middleware presentati in questa tesi integrano il concetto di VoI sia a livello di servizio che a livello di gestione per selezionare le informazioni più preziose per l'elaborazione e la diffusione, riducendo così il carico computazionale e garantendo una gestione ottimale dei dispositivi e della rete. Le ricerche presentate in questa tesi sono il risultato della collaborazione con istituti di ricerca internazionali e di un periodo di ricerca trascorso presso il Florida Institute for Human and Machine Cognition (IHMC), FL, USA.
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Ahlcrona, Felix. "Sakernas Internet : En studie om vehicular fog computing påverkan i trafiken." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15713.
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Framtidens fordon kommer vara väldigt annorlunda jämfört med dagens fordon. Stor del av förändringen kommer ske med hjälp av IoT. Världen kommer bli oerhört uppkopplat, sensorer kommer kunna ta fram data som de flesta av oss inte ens visste fanns. Mer data betyder även mer problem. Enorma mängder data kommer genereras och distribueras av framtidens IoT-enheter och denna data behöver analyseras och lagras på effektiva sätt med hjälp av Big data principer. Fog computing är en utveckling av Cloud tekniken som föreslås som en lösning på många av de problem IoT lider utav. Är tradionella lagringsmöjligheter och analyseringsverktyg tillräckliga för den enorma volymen data som kommer produceras eller krävs det nya tekniker för att stödja utvecklingen? Denna studie kommer försöka besvara frågeställningen: ”Vilka problem och möjligheter får utvecklingen av Fog computing i personbilar för konsumenter?” Frågeställningen besvaras genom en systematisk litteraturstudie. Den systematiska litteraturstudien syfte är identifiera och tolka tidigare litteratur och forskning. Analys av materialet har skett med hjälp av öppen kodning som har använts för att sortera och kategorisera data. Resultat visar att tekniker som IoT, Big data och Fog computing är väldigt integrerade i varandra. I framtidens fordon kommer det finns mycket IoTenheter som producerar enorma mängder data. Fog computing kommer bli en effektiv lösning för att hantera de mängder data från IoT-enheterna med låg fördröjning. Möjligheterna blir nya applikationer och system som hjälper till med att förbättra säkerheten i trafiken, miljön och information om bilens tillstånd. Det finns flera risker och problem som behöver lösas innan en fullskalig version kan börja användas, risker som autentisering av data, integriteten för användaren samt bestämma vilken mobilitetsmodell som är effektivast.Future vehicles will be very different from today's vehicles. Much of the change will be done using the IoT. The world will be very connected, sensors will be able to access data that most of us did not even know existed. More data also means more problems. Enormous amounts of data will be generated and distributed by the future's IoT devices, and this data needs to be analyzed and stored efficiently using Big data Principles. Fog computing is a development of Cloud technology that is suggested as a solution to many of the problems IoT suffer from. Are traditional storage and analysis tools sufficient for the huge volume of data that will be produced or are new technologies needed to support development? This study will try to answer the question: "What problems and opportunities does the development of Fog computing in passenger cars have for consumers?" The question is answered by a systematic literature study. The objective of the systematic literature study is to identify and interpret previous literature and research. Analysis of the material has been done by using open coding where coding has been used to sort and categorize data. Results show that technologies like IoT, Big data and Fog computing are very integrated in each other. In the future vehicles there will be a lot of IoT devices that produce huge amounts of data. Fog computing will be an effective solution for managing the amount of data from IoT devices with a low latency. The possibilities will create new applications and systems that help improve traffic safety, the environment and information about the car's state and condition. There are several risks and problems that need to be resolved before a full-scale version can be used, such as data authentication, user integrity, and deciding on the most efficient mobility model.
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Ahmed, Arif. "Efficient cloud application deployment in distributed fog infrastructures." Thesis, Rennes 1, 2020. http://www.theses.fr/2020REN1S004.
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Les architectures Fog computing sont composées d'un grand nombre de machines dispersées dans une zone géographique telle qu'une ville ou une région. Dans ce contexte il est important de permettre un démarrage rapide des applications déployées sous forme de containers Docker. Cette thèse étudie les raisons de la lenteur de déploiement, et identifie trois opportunités susceptibles de réduire le temps de déploiement des conteneurs: (1) améliorer le taux de réussite du cache Docker; (2) accélérer l'opération d'installation d'une image; et (3) accélérer le processus de démarrage après la création d'un conteneurFog computing architectures are composed of a large number of machines distributed across a geographical area such as a city or a region. In this context it is important to support a quick startup of applications deployed in the for of docker containers. This thesis explores the reasons for slow deployment and identifies three improvement opportunities: (1) improving the Docker cache hit rate; (2) speed-up the image installation operation; and (3) accelerate the application boot phase after the creation of a container
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Jalew, Esubalew Alemneh. "Fog Computing based traffic Safety for Connected Vulnerable Road Users." Thesis, Bourgogne Franche-Comté, 2019. http://www.theses.fr/2019UBFCK057/document.
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Chaque année, des millions de personnes meurent et beaucoup d'autres subissent des séquelles graves à la suite d'accidents de la route. Malgré une multitude d’initiatives, le nombre de cas mortels et d'accidents graves augmente chaque année en engendrant des problèmes préoccupants à la fois sociaux, économiques et sanitaires. En raison de leur nombre élevé et de l'absence de protection personnelle, plus de la moitié de ces décès concerne les usagers vulnérables (en anglais, vulnerable road users - VRU) regroupant les piétons, cyclistes et motocyclistes. Les appareils mobiles, combinés à la technologie de Fog Computing (ou informatique géodistribuée, ou même informatique en brouillard), représentent une solution réaliste à court terme pour les protéger en les avertissant de l’imminence d'un accident de circulation. L’omniprésence des appareils mobiles et leurs capacités de calcul élevées font de ces appareils un élément important à considérer dans les solutions de sécurité routière. Le Fog Computing offre des fonctionnalités adaptées aux applications de sécurité routière, puisqu’il s’agit d’une extension du Cloud Computing permettant de rapprocher les services informatiques, le stockage et le réseau au plus près des utilisateurs finaux. Par conséquent, dans cette thèse, nous proposons une architecture réseau sans infrastructure supplémentaire (PV-Alert) pour des fins de sécurité routière et reposant uniquement sur les appareils mobiles des VRU et des conducteurs sur la route avec l’aide du concept de Fog Computing. Les données géographiques et cinématiques de ces appareils sont collectées et envoyées périodiquement au serveur fog situé à proximité. Le serveur fog traite ces données en exécutant un algorithme de calcul de risque d’accident de circulation et renvoie des notifications en cas d'accident imminent. L’évaluation de cette architecture montre qu’elle est capable de générer des alertes en temps réel et qu’elle est plus performante que d’autres architectures en termes de fiabilité, d’évolutivité et de latenceAnnually, millions of people die and many more sustain non-fatal injuries because of road traffic crashes. Despite multitude of countermeasures, the number of causalities and disabilities owing to traffic accidents are increasing each year causing grinding social, economic, and health problems. Due to their high volume and lack of protective-shells, more than half of road traffic deaths are imputed to vulnerable road users (VRUs): pedestrians, cyclists and motorcyclists. Mobile devices combined with fog computing can provide feasible solutions to protect VRUs by predicting collusions and warning users of an imminent traffic accident. Mobile devices’ ubiquity and high computational capabilities make the devices an important components of traffic safety solutions. Fog computing has features that suits to traffic safety applications as it is an extension of cloud computing that brings down computing, storage, and network services to the proximity of end user. Therefore, in this thesis, we have proposed an infrastructure-less traffic safety architecture that depends on fog computing and mobile devices possessed by VRUs and drivers. The main duties of mobile devices are extracting their positions and other related data and sending cooperative awareness message to a nearby fog server using wireless connection. The fog server estimates collision using a collision prediction algorithm and sends an alert message, if an about-to-occur collision is predicted. Evaluation results shows that the proposed architecture is able to render alerts in real time. Moreover, analytical and performance evaluations depict that the architecture outperforms other related road safety architectures in terms of reliability, scalability and latency. However, before deploying the architecture, challenges pertaining to weaknesses of important ingredients of the architecture should be treated prudently. Position read by mobile devices are not accurate and do not meet maximum position sampling rates traffic safety applications demand. Moreover, continuous and high rate position sampling drains mobile devices battery quickly. From fog computing’s point of view, it confronts new privacy and security challenges in addition to those assumed from cloud computing. For aforementioned challenges, we have proposed new solutions: (i) In order to improve GPS accuracy, we have proposed an efficient and effective two-stage map matching algorithm. In the first stage, GPS readings obtained from smartphones are passed through Kalman filter to smooth outlier readings. In the second stage, the smoothed positions are mapped to road segments using online time warping algorithm. (ii) position sampling frequency requirement is fulfilled by an energy efficient location prediction system that fuses GPS and inertial sensors’ data. (iii) For energy efficiency, we proposed an energy efficient fuzzy logic-based adaptive beaconing rate management that ensures safety of VRUs. (iv) finally, privacy and security issues are addressed indirectly using trust management system. The two-way subjective logic-based trust management system enables fog clients to evaluate the trust level of fog servers before awarding the service and allows the servers to check out the trustworthiness of the service demanders. Engaging omnipresent mobile device and QoS-aware fog computing paradigm in active traffic safety applications has the potential to reduce overwhelming number of traffic accidents on VRUs
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Holm, Rasmus. "The fog-unit : Evaluation of the fog-unit’s effect on network performance." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-34048.
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Today at various locations and factories we have a lot of sensors and actuators that interact with each other and a control-unit. The control-unit is in most cases a cloud-based solution. This is in most cases a good solution. However, there is a rise in expected devices and sensors which will most likely be too much data for the existing network to handle. This paper researches if a fog-unit might be the solution to this problem. The setup of the fog-unit in the network is a unit between the cloud and the sensors and actuators. In this paper the fog-unit and sensors/actuators have been emulated on Raspberry Pi’s. The sensors are emulated using python-threads and communicate with the fog-unit using the UDP-based protocol CoAP and the fog communicates to the cloud using the TCP- based protocol MQTT. After a prototype was built it using said Raspberry Pi’s it was sent through a few measurements in the fields of bandwidth, cloud-utilization and response times. This was later compared to another setup without the fog-unit as the control setup. The result with this kind of setup was that a fog-unit lowers the cloud-utilization and use of bandwidth, however it increases the round trip time of a request from the cloud by a large amount. Which leads to the conclusion that a fog-unit in this kind of setup might be a good network solution if the response time to the cloud isn’t important.
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Segura, Danilo Costa Marim. "Integrando grades móveis em uma arquitetura orientada a serviços." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13122016-095843/.
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O aumento no número de dispositivos móveis, como smartphones, tablets e laptops, e o avanço em seu potencial computacional permitiu considerá-los como recursos computacionais. O uso de recursos computacionais com maior proximidade vem crescendo ano após ano, sendo chamado de Fog computing, em que os elementos na borda da Internet são explorados, uma vez que os serviços computacionais convencionais podem estar indisponíveis ou sobrecarregados. Dessa forma, este projeto de Mestrado tem como foco possibilitar o uso de dispositivos móveis no provimento de serviços computacionais entre si de forma colaborativa através da heurística Maximum Regret adaptada, que busca alocar tarefas computacionais em dispositivos locais de forma a minimizar o consumo de energia e evitar dispositivos não confiáveis. Também há uma meta-heurística em um nível global, que interconecta os diferentes aglomerados de dispositivos móveis na borda da Internet, e possui informações globais de Quality of Service (QoS). Foram realizados experimentos que mostraram que evitar dispositivos móveis como recursos com um baixo grau de confiabilidade possibilitou diminuir o impacto no consumo de energia, além de ser possível diminuir os tempos de resposta e de comunicação ao ajustar a política de seleção de aglomerados externos.The increasing number of mobile devices, such as smartphones, tablets and laptops, as well as advances in their computing power have enabled us to consider them as resources, exploring the proximity. The use of near computing resources is growing year by year, being called as Fog computing, where the elements on the edge of the Internet are exploited, once the computer services providers could be unavailable or overloaded. Thus, this Masters project focuses on using mobile devices to provide computing services among them through a heuristic called Adapted Maximum Regret, which tries to minimize energy consumption and avoid untrustable devices. There is also top-level metaheuristic which interconnects different clusters of devices on the edge of the Internet with global information to guarantee Quality of Services (QoS). We conducted a set of experiments that showed us to avoid devices with a high degree of failures to save more energy when allocating tasks among them, as well as decreasing the applications response time and communication through adjusts in the selection algorithm of external agglomerates.
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Shirin, Abkenar Forough. "Towards Hyper-efficient IoT Networks Using Fog Paradigm." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/28951.
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Fog computing was emerged as a treasured paradigm to improve the efficiency of the typical cloud of things (CoT) architecture of the Internet of Things (IoT) networks. Contrasting to the CoT in which the resource-rich high-performance data centers (DCs) are located far from the energy-constrained terminal nodes (TNs), fog nodes (FNs) in fog-enabled architecture provide computing resources in the proximity of the TNs. Therefore, the TNs consume less energy to offload their generated tasks to the FNs rather than the cloud DCs. Moreover, shortening the distance between the TNs and the FNs results in alleviating the transmission latency for the delay-sensitive tasks generated by the TNs. This is more significant for specific applications, such as smart healthcare, search and rescue, and disaster management, wherein making a prompt decision is vital to save lives. However, Fog-IoT networks still suffer from challenges regarding energy efficiency and provisioning quality of service (QoS) requirements, especially in terms of delay and throughput. The motivation behind this thesis is to tackle the corresponding challenges and improve the performance of the Fog-IoT networks. To this end, novel optimization problems, models, methods, and algorithms are proposed that mainly focus on the energy efficiency improvement and QoS provisioning in Fog-IoT networks. Moreover, due to the importance of the mobility of FNs, the contributions of the thesis encompass improving the performance of Fog-IoT networks with respect to both fixed and mobile FNs.
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Zaripov, Behruz. "Analysis of Fog Networking Procedures in Heterogeneous Wireless Networks." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017.
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The purpose of this study is to provide a general framework of the latest trends of mobile network architectures. The two main architectures treated in this work are Cloud-RAN and Fog-RAN. We give descriptions of both architectures, then show advantages and disadvantages of them. We mainly focus on the performance of Fog-RAN model taking into account only computation and communication latencies. In order to analyse our Fog-RAN architecture, we measure the impact of traffic produced in our network, by using 3 different policies: Random Policy, Maximum Available Capacity Policy and Nearest Node Policy. Furthermore, we measure the impact of delay by fixing the amount of traffic generated by the network. Numerical results of our considered scenarios show that the maximum available capacity policy outperforms two other polices, when the traffic produced in the network is very high. When the traffic is very low, the best policy is the nearest node one. On the other hand, by fixing the amount of traffic we show that when the delay threshold is from 1-3 ms the Maximum capacity policy performs better than two other policies. When the delay threshold is greater than 5 ms the Nearest Node policy shows better results.
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Sellami, Youssef. "Secure data management in an IoT-Fog/Edge computing architecture." Electronic Thesis or Diss., Valenciennes, Université Polytechnique Hauts-de-France, 2024. https://ged.uphf.fr/nuxeo/site/esupversions/14bb8a1d-7fbb-4d10-a7e7-99650617c232.
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L'internet des objets vise à intégrer les mondes physique et numérique dans un écosystème unique en interconnectant un grand nombre d'objets intelligents (capteurs, smartphones, véhicules autonomes, etc.) à l'internet. Cependant, la quantité massive de données est l'une des conséquences inévitables de la croissance du nombre d'objets connectés. L'évolution de l'IoT et de ses applications dans les années à venir (industrie 4.0, villes intelligentes) nécessite une gestion des données adaptée aux capacités limitées des objets connectés. De nouveaux paradigmes de traitement et de communication, tels que le fog/edge computing, sont à l'étude pour répondre aux attentes des applications et de leurs utilisateurs. Ces architectures utilisent des composants (routeurs, stations de base, machines utilisateurs, etc.) situés à proximité des objets et de l'utilisateur final. Cependant, ce couplage de l'IoT-Fog/Edge n'intègre pas encore de mécanismes de sécurité suffisamment robustes au regard des environnements de déploiement visés et des applications critiques qu'ils devront supporter. Cette thèse explore tout d'abord les architectures émergentes de l'IoT-edge/fog et met en évidence les différents défis et problèmes de sécurité posés par ce paradigme. L'un des problèmes critiques identifiés est la garantie de l'intégrité des données dans le fog. Malheureusement, les auditeurs tiers centralisés traditionnels sont inefficaces en raison de la latence élevée du réseau et des contraintes associées. Par conséquent, nous proposons un protocole de vérification publique efficace qui s'appuie sur le problème Short Integer Solution et sur des signatures basées sur l'identité. Ce nouveau protocole garantit l'intégrité et l'authenticité des données, autorise les modifications légitimes des données et permet une vérification distribuée de l'intégrité des données sans dépendre d'un tiers de confiance. Nous abordons également dans cette thèse la question de la fiabilité des données dans le fog, qui est cruciale pour la fiabilité des événements partagés entre les nœuds de fog et les sources de données. Une nouvelle solution basée sur la blockchain est présentée pour créer un environnement transparent et traçable permettant d'évaluer la fiabilité des données, de préserver les scores de confiance et d'encourager la responsabilité. Notre modèle calcule les scores de confiance sur la base de facteurs tels que la plausibilité de l'événement, la pertinence temporelle et la pertinence de la distance afin d'identifier efficacement les entités malveillantes et d'encourager un comportement digne de confiance. Enfin, nous avons mis l'accent dans cette thèse sur la protection de la confidentialité des données contre la menace quantique dans le contexte Edge/IoT. En outre, plusieurs schémas cryptographiques post-quantiques ont été proposés dans la littérature, visant à développer des techniques de cryptage résistantes à de telles attaques. En raison de ses propriétés de sécurité prometteuses, NTRU a été sélectionné comme candidat lors de la phase finale du concours du NIST sur la cryptographie post-quantique. Toutefois, cette méthode pose des problèmes pour les objets IoT en raison de ses exigences potentiellement plus élevées en matière de calcul et de mémoire. Motivés par la nécessité d'augmenter la durée de vie des objets IoT tout en étant capables de résister aux attaques quantiques, nous proposons un nouveau schéma collaboratif basé sur NTRU. Notre schéma préserve la confidentialité des données échangées entre les objets IoT déployés dans l'architecture edge. En outre, notre schéma répartit la charge des opérations cryptographiques entre les nœuds du edge et les objets IoT. Cette approche collaborative permet aux objets IoT de réduire considérablement leurs coûts de calcul tout en garantissant la confidentialité des données. En outre, la répartition proposée du calcul permet l'évolutivité de l'architecture et améliore la durabilité des environnements IoTThe Internet of Things (IoT) aims to integrate the physical and digital worlds into a single ecosystem by interconnecting a large number of intelligent objects (sensors/actuators, smartphones, autonomous vehicles, etc.), to the internet. However, the massive amount of data is one of the inevitable consequences of the exponential growth in the number of connected objects. The evolution of the IoT and its applications in the years to come (industry 4.0, smart cities, intelligent transport) requires data management adapted to the limited capacities of connected objects. New processing and communication paradigms, such as fog or edge computing, are being studied to meet the expectations of applications and their users.These architectures use components (such as routers, base stations, user machines, etc.) located in close proximity to objects and end-user. However, this technological coupling of IoT and Fog/Edge computing does not yet incorporate sufficiently robust security mechanisms in view of the targeted deployment environments and the critical applications they will have to support.This thesis first explores the emerging IoT-edge and fog computing architectures and highlights the various security challenges and issues posed by this new paradigm. One of the critical problems identified is guaranteeing data integrity in the highly dynamic and distributed environment of fog computing. Unfortunately, the traditional centralized third-party auditors are ineffective due to high network latency and associated constraints. Therefore, to solve this issue, we propose an efficient public verification protocol leveraging the Short Integer Solution (SIS) problem and identity-based signatures. This new protocol ensures data integrity and authenticity, allows for legitimate data modifications, and enables distributed data integrity verification without relying on a trusted third party.Furthermore, we address in this thesis the data trustworthiness in fog computing systems, which is crucial for the reliability of events shared between fog nodes and data sources. A novel Blockchain-based solution is presented to create a transparent, traceable environment for evaluating event trustworthiness, preserving trust scores, and fostering accountability. Our model calculates trust scores based on factors such as event plausibility, temporal relevance and distance relevance to effectively identify malicious entities and encourage trustworthy behavior.Finally, we focused in this thesis on the protection of data confidentiality against the quantum threat in the Edge/IoT context. In addition, several post-quantum cryptographic schemes have been proposed in the literature, aiming to develop encryption techniques resistant to such attacks.Due to its promising security properties and efficiency against quantum attacks, NTRU was selected as a candidate in the final round of the NIST competition on post-quantum cryptography. However, this method poses challenges for constrained devices due to its potentially higher computational and memory requirements. Motivated by the necessity to increase the lifetime of resource-constrained IoT devices while being able to resist quantum attacks, we propose a new NTRU-based collaborative scheme. Our scheme preserves the confidentiality of sensitive information exchanged among constrained IoT devices deployed in an edge computing architecture. Moreover, it distributes the workload of the cryptographic operations across edge nodes and IoT devices within the same network. This collaborative approach allows IoT devices to significantly reduce their computational costs while guaranteeing data confidentiality. Furthermore, the proposed distribution of computing enables scalability of the architecture and improves the sustainability of IoT environments.Keywords: Fog computing, Edge computing, IoT, Data integrity, Security, Lattice-based cryptography, SIS problem, NTRU, Trust management, Confidentiality
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Xia, Ye. "Combining Heuristics for Optimizing and Scaling the Placement of IoT Applications in the Fog." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAM084/document.
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Alors que l’informatique en brouillard amène les ressources de traitement et de stockage à la périphérie du réseau, il existe un besoin croissant de placement automatisé (c.-à-d. La sélection de l'hôte) pour déployer des applications distribuées. Un tel placement doit être conforme aux besoins en ressources des applications dans une infrastructure de brouillard hétérogène et dynamique, et traiter la complexité apportée par les applications Internet des objets (IoT) liées aux capteurs / actionneurs. Cette thèse présente un modèle, une fonction objective et des heuristiques pour résoudre le problème de la mise en place d'applications IoT distribuées dans le brouillard. En combinant les heuristiques proposées, notre approche est capable de gérer les problèmes à grande échelle et de prendre efficacement des décisions de placement adaptées à l'objectif - en optimisant les performances des applications placées. L'approche proposée est validée par une analyse de complexité et une simulation comparative avec des tailles et des applications de tailles variablesAs fog computing brings processing and storage resources to the edge of the network, there is an increasing need of automated placement (i.e., host selection) to deploy distributed applications. Such a placement must conform to applications' resource requirements in a heterogeneous fog infrastructure, and deal with the complexity brought by Internet of Things (IoT) applications tied to sensors and actuators. This paper presents four heuristics to address the problem of placing distributed IoT applications in the fog. By combining proposed heuristics, our approach is able to deal with large scale problems, and to efficiently make placement decisions fitting the objective: minimizing placed applications' average response time. The proposed approach is validated through comparative simulation of different heuristic combinations with varying sizes of infrastructures and applications
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Guardo, Ermanno Lorenzo. "Edge Computing: challenges, solutions and architectures arising from the integration of Cloud Computing with Internet of Things." Doctoral thesis, Università di Catania, 2018. http://hdl.handle.net/10761/3908.
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The rapid spread of the Internet of Things (IoT) is causing the exponential growth of objects connected to the network, in fact, according to estimates, in 2020 there will be about 3/4 devices per person totaling of over 20 billion connected devices. Therefore, the use of content that requires intensive bandwidth consumption is growing.
In order to meet these growing needs, the computing power and storage space are transferred to the network edge to reduce the network latency and increase the bandwidth availability.
Edge computing allows to approach high-bandwidth content and sensitive apps to the user or data source and is preferred to use it for many IoT applications respect to cloud computing. Its distributed approach addresses the needs of IoT and industrial IoT, as well as the immense amount of data generated by smart sensors and IoT devices, which would be costly and time-consuming to send to the cloud for processing and analysis. Edge computing reduces both the bandwidth needed and the communication among sensors and cloud, which can negatively affect the IoT performance. The goal of edge computing is to improve efficiency and reduce the amount of data transported to the cloud for processing, analysis and storage.
The research activity carried out during the three years of the Ph.D. program focused on the study, design and development of architectures and prototypes based on the Edge Computing in various contexts such as smart cities and agriculture. Therefore, the well-known paradigms of Fog Computing and Mobile Edge Computing have been faced.
In this thesis, will be discussed the work carried out through the exploitation of the Fog Computing and Mobile Edge Computing paradigms, considered suitable solutions to address the challenges of the fourth industrial revolution.
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Bida, Mihail. "Tecniche di Drift Detection basate su Fog Computing per Scenari Industria 4.0." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23020/.
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Uno dei concetti più interessanti di Industria 4.0, quella che oggi viene intesa come quarta rivoluzione industriale, è il Digital Twin (gemello digitale), basato sull'idea che ogni parte fisica debba avere una rappresentazione nel mondo digitale.
Questo è permesso dalla grande quantità di dati della sensoristica, automaticamente generati e provenienti dai macchinari industriali.
Una sfaccettatura del Digital Twin, che si basa sull'analisi di questi flussi di dati con lo scopo di ottimizzazione dei processi produttivi, è la Predictive Maintenance.
Questa, consiste nell’effettuare diagnosi dei componenti e del macchinario tramite lo studio dei datastream in modo da individuare interventi di manutenzione soltanto quando strettamente necessario.
Questo studio si focalizza sulla regressione, una tecnica specifica basata sull'apprendimento automatico usato per identificare un concept drift, un cambiamento di concetto nei datastream in entrata, in modo da poter attivare azioni di manutenzione predittiva.
L'obiettivo è di riconoscere l'usura crescente che porterebbe il macchinario a un fallimento in modo da prevenirlo, cercando di discriminare tra dati sani di normale utilizzo e segnalare un cambio di concetto quando dati non visti o non sani vengono incontrati.
Si è costruita una pipeline composta da varie componenti estendibili e personalizzabili che permettono di scegliere i modelli di regressione da testare (e allenare) e di adattare le parti a stream differenti. Questa gestisce il flusso di dati dal macchinario fino all'analisi e all'eventuale allarme. L'architettura è stata pensata ed è stata fornita una sua reale implementazione su fog node tramite l'utilizzo di docker container.
Il tutto è stato testato e ne vengono mostrati i risultati utilizzando dati sintetizzati secondo la letteratura presente per i macchinari industriali.
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VENANZI, RICCARDO. "Device as a Service and Fog Computing Middleware for the Internet of Things." Doctoral thesis, Università degli studi di Ferrara, 2019. http://hdl.handle.net/11392/2488079.
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Nallendran, Vignesh Raja. "Predicting Performance Run-time Metrics in Fog Manufacturing using Multi-task Learning." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/102501.
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The integration of Fog-Cloud computing in manufacturing has given rise to a new paradigm called Fog manufacturing. Fog manufacturing is a form of distributed computing platform that integrates Fog-Cloud collaborative computing strategy to facilitate responsive, scalable, and reliable data analysis in manufacturing networks. The computation services provided by Fog-Cloud computing can effectively support quality prediction, process monitoring, and diagnosis efforts in a timely manner for manufacturing processes. However, the communication and computation resources for Fog-Cloud computing are limited in Fog manufacturing. Therefore, it is significant to effectively utilize the computation services based on the optimal computation task offloading, scheduling, and hardware autoscaling strategies to finish the computation tasks on time without compromising on the quality of the computation service. A prerequisite for adapting such optimal strategies is to accurately predict the run-time metrics (e.g., Time-latency) of the Fog nodes by capturing their inherent stochastic nature in real-time. It is because these run-time metrics are directly related to the performance of the computation service in Fog manufacturing. Specifically, since the computation flow and the data querying activities vary between the Fog nodes in practice. The run-time metrics that reflect the performance in the Fog nodes are heterogenous in nature and the performance cannot be effectively modeled through traditional predictive analysis. In this thesis, a multi-task learning methodology is adopted to predict the run-time metrics that reflect performance in Fog manufacturing by addressing the heterogeneities among the Fog nodes. A Fog manufacturing testbed is employed to evaluate the prediction accuracies of the proposed model
and benchmark models. The proposed model can be further extended in computation tasks offloading and architecture optimization in Fog manufacturing to minimize the time-latency and improve the robustness of the system.Master of Science
Smart manufacturing aims at utilizing Internet of things (IoT), data analytics, cloud computing, etc. to handle varying market demand without compromising the productivity or quality in a manufacturing plant. To support these efforts, Fog manufacturing has been identified as a suitable computing architecture to handle the surge of data generated from the IoT devices. In Fog manufacturing computational tasks are completed locally through the means of interconnected computing devices called Fog nodes. However, the communication and computation resources in Fog manufacturing are limited. Therefore, its effective utilization requires optimal strategies to schedule the computational tasks and assign the computational tasks to the Fog nodes. A prerequisite for adapting such strategies is to accurately predict the performance of the Fog nodes. In this thesis, a multi-task learning methodology is adopted to predict the performance in Fog manufacturing. Specifically, since the computation flow and the data querying activities vary between the Fog nodes in practice. The metrics that reflect the performance in the Fog nodes are heterogenous in nature and cannot be effectively modeled through conventional predictive analysis. A Fog manufacturing testbed is employed to evaluate the prediction accuracies of the proposed model and benchmark models. The results show that the multi-task learning model has better prediction accuracy than the benchmarks and that it can model the heterogeneities among the Fog nodes. The proposed model can further be incorporated in scheduling and assignment strategies to effectively utilize Fog manufacturing's computational services.
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Schenfeld, Matheus Crespi. "Fog e edge computing : uma arquitetura h?brida em um ambiente de internet das coisas." Pontif?cia Universidade Cat?lica do Rio Grande do Sul, 2017. http://tede2.pucrs.br/tede2/handle/tede/7730.
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Internet of Things (IoT) is considered a computational evolution that advocates the existence of a large number of physical objects embedded with sensors and actuators, connected by wireless networks and communicating through the Internet. From the beginning of the concept to the present day, IoT is widely used in the various sectors of industry and also in academia. One of the needs encountered in these areas was to be connected to IoT devices or subsystems throughout the world. Thus, cloud computing gains space in these scenarios where there is a need to be connected and communicating with a middleware to perform the data processing of the devices. The concept of cloud computing refers to the use of memory, storage and processing of shared resources, interconnected by the Internet. However, IoT applications sensitive to communication latency, such as medical emergency applications, military applications, critical security applications, among others, are not feasible with the use of cloud computing, since for the execution of all calculations and actions messaging between devices and the cloud is required. Solving this limitation found in the use of cloud computing, the concept of fog computing arises and whose main idea is to create a federated processing layer, still in the local network of the computing devices of the ends of the network. In addition to fog computing, there is also edge computing operating directly on the devices layer, performing some kind of processing, even with little computational complexity, in order to further decrease the volume of communication, besides collaborating to provide autonomy in decision making yet in the Things layer. A major challenge for both fog and edge computing within the IoT scenario is the definition of a system architecture that can be used in different application domains, such as health, smart cities and others. This work presents a system architecture for IoT devices capable of enabling data processing in the devices themselves or the closest to them, creating the edge computing layer and fog computing layer that can be applied in different domains, improving Quality of Services (QoS) and autonomy in decision making, even if the devices are temporarily disconnected from the network (offline). The validation of this architecture was done within two application scenarios, one of public lighting in smart city environment and another simulating an intelligent agricultural greenhouse. The main objectives of the tests were to verify if the use of the concepts of edge and fog computing improve system efficiency compared to traditional IoT architectures. The tests revealed satisfactory results, improving connection times, processing and delivery of information to applications, reducing the volume of communication between devices and core middleware, and improving communications security. It also presents a review of related work in both academia and industry.
Internet das Coisas (IoT) ? considerada uma evolu??o computacional que preconiza a exist?ncia de uma grande quantidade de objetos f?sicos embarcados com sensores e atuadores, conectados por redes sem fio e que se comunicam atrav?s da Internet. Desde o surgimento do conceito at? os dias atuais, a IoT ? amplamente utilizada nos diversos setores da ind?stria e tamb?m no meio acad?mico. Uma das necessidades encontradas nessas ?reas foi a de estar conectado com dispositivos ou subsistemas de IoT espalhados por todo o mundo. Assim, cloud computing ganha espa?o nesses cen?rios, onde existe a necessidade de estar conectado e se comunicando com um middleware para realizar o processamento dos dados dos dispositivos. O conceito de cloud computing refere-se ao uso de mem?ria, armazenamento e processamento de recursos compartilhados, interligados pela Internet. No entanto, aplica??es IoT sens?veis ? lat?ncia de comunica??o, tais como, aplica??es m?dico-emergenciais, aplica??es militares, aplica??es de seguran?a cr?tica, entre outras, s?o invi?veis com o uso de cloud computing, visto que para a execu??o de todos os c?lculos e a??es ? necess?ria a troca de mensagens entre dispositivos e nuvem. Solucionando essa limita??o encontrada na utiliza??o de cloud computing, surge o conceito de fog computing, cuja ideia principal ? criar uma camada federada de processamento ainda na rede local dos dispositivos de computa??o das extremidades da rede. Al?m de fog computing tamb?m surge edge computing operando diretamente na camada dos dispositivos, realizando algum tipo de processamento, mesmo que de pouca complexidade computacional, a fim de diminuir ainda mais o volume de comunica??o, al?m de colaborar para prover autonomia na tomada de decis?es ainda na camada das coisas. Um grande desafio tanto para fog quanto para edge computing dentro do cen?rio de IoT ? a defini??o de uma arquitetura de sistema que possa ser usada em diferentes dom?nios de aplica??o, como sa?de, cidades inteligentes entre outros. Esse trabalho apresenta uma arquitetura de sistema para dispositivos IoT capaz de habilitar o processamento de dados nos pr?prios dispositivos ou o mais pr?ximo deles, criando a camada de edge e fog computing que podem ser aplicadas em diferentes dom?nios, melhorando a Qualidade dos Servi?os (QoS) e autonomia na tomada de decis?o, mesmo se os dispositivos estiverem temporariamente desconectados da rede (offline). A valida??o dessa arquitetura foi feita dentro de dois cen?rios de aplica??o, um de ilumina??o p?blica em ambiente de IoT e outro simulando uma estufa agr?cola inteligente. Os principais objetivos das execu??es dos testes foram verificar se a utiliza??o dos conceitos de edge e fog computing melhoram a efici?ncia do sistema em compara??o com arquiteturas tradicionais de IoT. Os testes revelaram resultados satisfat?rios, melhorando os tempos de conex?o, processamento e entrega das informa??es ?s aplica??es, redu??o do volume de comunica??o entre dispositivos e core middleware, al?m de melhorar a seguran?a nas comunica??es. Tamb?m ? apresentada uma revis?o de trabalhos relacionados tanto no meio acad?mico como no da ind?stria.
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Solimando, Michele. "Infrastrutture basate su Edge Computing per Supporto a Servizi Mobili in Ambienti Ostili." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/11331/.
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Questa tesi è incentrata sulla revisione del classico modello di infrastruttura Cloud. Le motivazioni sono da ricercare nelle condizioni operative reali della maggior parte dei dispositivi connessi alla rete attualmente. Si parla di ambiente ostile riferendosi a network popolate da molti dispositivi dalle limitate caratteristiche tecniche e spesso collegati con canali radio, molto più instabili delle connessioni cablate. Allo scenario va ad aggiungersi la necessità crescente di mobilità che limita ulteriormente i vantaggi derivanti dall'utilizzo dell’infrastruttura Cloud originale. La trattazione propone il modello Edge come estensione del Cloud. Esso ne amplia il ventaglio di utilizzo, favorendo aree di applicazione che stanno acquisendo maggiore influenza negli ultimi periodi e che richiedono una revisione delle vecchie infrastrutture Cloud, dettata dalle caratteristiche stringenti che necessitano per un'operatività soddisfacente.
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Ramalho, Fl?vio de Sousa. "SmartEdge: fog computing cloud extensions to support latency-sensitive IoT applications." PROGRAMA DE P?S-GRADUA??O EM SISTEMAS E COMPUTA??O, 2016. https://repositorio.ufrn.br/jspui/handle/123456789/22557.
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O r?pido crescimento do n?mero de dispositivos conectados ? Internet, associado ?s taxas crescentes de popularidade e demanda de aplica??es e servi?os em tempo real na nuvem, com restri??es de lat?ncia, torna muito dif?cil para estruturas de computa??o em nuvem tradicionais acomod?-los de forma eficiente. Mais especificamente, a abordagem centralizada adotada tradicionalmente por Data Centers (DC) atuais apresentam problemas de desempenho para atender de aplica??es em nuvem com alta densidade, principalmente quanto a capacidade de resposta e escalabilidade. Nossa depend?ncia insubstitu?vel por computa??o em nuvem, exige infra-estruturas de DCs sempre dispon?veis, enquanto mant?m ao mesmo tempo capacidades de desempenho suficientes para responder a uma enorme quantidade de solicita??es de aplicativos em nuvem. Neste trabalho, a aplicabilidade do emergente paradigma de computa??o em n?voa ? explorada para melhorar o desempenho no suporte de aplica??es em nuvem sens?veis ? lat?ncia voltadas a Internet das Coisas (do ingl?s Internet of Things - IoT). Com base neste objetivo, apresentamos o novo modelo denominado Infraestrutura de Borda como um Servi?o (do ingl?s Edge Infrastructure as a Service - EIaaS), que procura oferecer um novo modelo de computa??o em nuvem com servi?o de entrega baseado em computa??o de borda voltado a atender de forma eficiente as exig?ncias de aplica??es IoT em tempo real sens?veis ? lat?ncia. Com a abordagem EIaaS, provedores de nuvem podem implantar dinamicamente aplica??es/servi?os IoT diretamente nas infra-estruturas de computa??o de borda, nem como gerir seus recursos de n?vem/rede em tempo de execu??o, como forma de manter as aplica??es IoT sempre melhor conectadas e melhor servidas. A abordagem resultante ? arquitetada em uma estrutura modular, tendo como base tecnol?gica ferramentas de Rede Definida por Software (do ingl?s, Software- Defined Networking - SDN) para lidar com recursos de computa??o de borda (CPU, mem?ria, etc.) e de rede (caminhos, largura de banda, etc.), respectivamente. Os resultados preliminares mostram como as principais t?cnicas de virtualiza??o utilizadas no ?mbito deste trabalho, afetam o desempenho das aplica??es na infraestrutura de borda da rede. A virtualiza??o por containers leva vantagem sobre a t?cnica de virtualiza??o por m?quinas virtuais para implantar aplica??es na borda da rede, uma vez que oferece grande flexibilidade mesmo na presen?a de demanda de recursos.
The rapid growth in the number of Internet-connected devices, associated to the increasing rates in popularity and demand for real-time and latency-constrained cloud application services makes the use of traditional cloud computing frameworks challenging to afford such environment. More specifically, the centralized approach traditionally adopted by current Data Center (DC) pose performance issues to suit a high density of cloud applications, mainly in terms to responsiveness and scalability. Our irreplaceable dependency on cloud computing, demands DC infrastructures always available while keeping, at the same time, enough performance capabilities for responding to a huge amount of cloud application requests. In this work, the applicability of the fog computing emerging paradigm is exploited to enhance the performance on supporting latency-sensitive cloud applications tailored for Internet of Things (IoT).With this goal in mind, we introduce a new service model named Edge Infrastructure as a Service (EIaaS), which seeks to offer a new edge computing tailored cloud computing service delivery model to efficiently suit the requirements of the real-time latency-sensitive IoT applications. With EIaaS approach, cloud providers are allowed to dynamically deploy IoT applications/services in the edge computing infrastructures and manage cloud/network resources at the run time, as means to keep IoT applications always best connected and best served. The resulting approach is modeled in a modular architecture, leveraging both container and Software-Defined Networking technologies to handle edge computing (CPU, memory, etc) and network resources (path, bandwidth, etc) respectively. Preliminary results show how the virtualization technique affects the performance of applications at the network edge infra. The container-based virtualization takes advantage over the hypervisor-based technique for deploying applications at the edge computing infrastructure, as it offers a great deal of flexibility under the presence of resource constraints.
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ZHANG, TIANZHU. "Control plane optimization in Software Defined Networking and task allocation for Fog Computing." Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2706750.
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As the next generation of mobile wireless standard, the fifth generation (5G) of cellular/wireless network has drawn worldwide attention during the past few years. Due to its promise of higher performance over the legacy 4G network, an increasing number of IT companies and institutes have started to form partnerships and create 5G products. Emerging techniques such as Software Defined Networking and Mobile Edge Computing are also envisioned as key enabling technologies to augment 5G competence. However, as popular and promising as it is, 5G technology still faces several intrinsic challenges such as (i)
the strict requirements in terms of end-to-end delays, (ii) the required reliability in the control plane and (iii) the minimization of the energy consumption. To cope with these daunting issues, we provide the following main contributions.
As first contribution, we address the problem of the optimal placement of SDN controllers. Specifically, we give a detailed analysis of the impact that controller placement imposes on the reactivity of SDN control plane, due to the consistency protocols adopted to manage the data structures that are shared across different controllers. We compute the Pareto frontier, showing all the possible tradeoffs achievable between the inter-controller delays and the switch-to-controller latencies. We define two data-ownership models and formulate the controller placement problem with the goal of minimizing the reaction time of control plane, as perceived by a switch. We propose two evolutionary algorithms, namely Evo-Place and Best-Reactivity, to compute the Pareto frontier and the controller placement minimizing the reaction time, respectively. Experimental results show that Evo-Place outperforms its random counterpart, and Best-Reactivity can achieve a relative error of <= 30% with respect to the optimal algorithm by only sampling less than 10% of the whole solution space.
As second contribution, we propose a stateful SDN approach to improve the scalability of traffic classification in SDN networks. In particular, we leverage the OpenState extension to OpenFlow to deploy state machines inside the switch and minimize the number of packets redirected to the traffic classifier. We experimentally compare two approaches, namely Simple Count-Down (SCD) and Compact Count-Down (CCD), to scale the traffic classifier and minimize the flow table occupancy.
As third contribution, we propose an approach to improve the reliability of SDN controllers. We implement BeCheck, which is a software framework to detect ``misbehaving'' controllers. BeCheck resides transparently between the control plane and data plane, and monitors the exchanged OpenFlow traffic messages. We implement three policies to detect misbehaving controllers and forward the intercepted messages. BeCheck along with the different policies are validated in a real test-bed. As fourth contribution, we investigate a mobile gaming scenario in the context of fog computing, denoted as Integrated Mobile Gaming (IMG) scenario. We partition mobile games into individual tasks and cognitively offload them either to the cloud or the neighbor mobile devices, so as to achieve minimal energy consumption. We formulate the IMG model as an ILP problem and propose a heuristic named Task Allocation with Minimal Energy cost (TAME). Experimental results show that TAME approaches the optimal solutions while outperforming two other state-of-the-art task offloading algorithms.
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Chakraborty, Suryadip. "Data Aggregation in Healthcare Applications and BIGDATA set in a FOG based Cloud System." University of Cincinnati / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1471346052.
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Bhowmick, Satyajit. "A Fog-based Cloud Paradigm for Time-Sensitive Applications." University of Cincinnati / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1467988828.
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Manzalini, Antonio. "An operating system for 5G Edge Clouds." Thesis, Evry, Institut national des télécommunications, 2016. http://www.theses.fr/2016TELE0013.
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La technologie et les conducteurs socio-économiques créent les conditions d'une transformation profonde, appelée "Softwarization", du Telco et des TIC. Réseaux définis par logiciel et réseau Fonctions de virtualisation sont deux des principales technologies permettant ouvrant la voie à cette transformation. Softwarization permettra de virtualiser toutes les fonctions de réseau et de services d'une infrastructure de Telco et de les exécuter sur une plates-formes logicielles, entièrement découplés de l'infrastructure physique sous (presque basé sur du matériel standard). Tous les services seront fournis en utilisant un «continuum» des ressources virtuelles (traitement, de stockage et de communication) avec un investissement en capital initial pratiquement très limité et avec des coûts d'exploitation modestes. 5G sera la première exploitation de Softwarization. 5G sera une infrastructure distribuée massivement dense, intégrant le traitement, le stockage et (fixes et radio) des capacités de mise en réseau. En résumé, l'objectif général de cette thèse a étudié les défis techniques et les opportunités d'affaires apportées par le "Softwarization" et 5G. En particulier, la thèse propose que le 5G devra avoir une sorte de système d'exploitation (5GOS) capable de fonctionner les RAN et de base et les infrastructures fixes convergés. Les contributions de cette thèse ont été: 1) définir une vision pour les futures infrastructures 5G, des scénarios, des cas d'utilisation et les exigences principales: 2) définissant l'architecture fonctionnelle d'un système d'exploitation pour 5G; 3) la conception de l'architecture logicielle d'un 5GOS pour le "bord Cloud"; 4) comprendre les impacts technico-économiques de la vision et 5GOS, et les stratégies les plus efficaces pour l'exploiterTechnology and socio-economic drivers are creating the conditions for a profound transformation, called “Softwarization”, of the Telco and ICT. Software-Defined Networks and Network Functions Virtualization are two of the key enabling technologies paving the way towards this transformation. Softwarization will allow to virtualize all network and services functions of a Telco infrastructure and executing them onto a software platforms, fully decoupled from the underneath physical infrastructure (almost based on standard hardware). Any services will be provided by using a “continuum” of virtual resources (processing, storage and communications) with practically very limited upfront capital investment and with modest operating costs. 5G will be the first exploitation of Softwarization. 5G will be a massively dense distributed infrastructure, integrating processing, storage and (fixed and radio) networking capabilities. In summary, the overall goal of this thesis has been investigating technical challenges and business opportunities brought by the “Softwarization” and 5G. In particular, the thesis proposes that the 5G will have to have a sort of Operating System (5GOS) capable of operating the converged fixed and RAN and core infrastructures. Main contributions of this thesis have been: 1) defining a vision for future 5G infrastructures, scenarios, use-cases and main requirements; 2) defining the functional architecture of an Operating System for 5G; 3) designing the software architecture of a 5G OS for the “Edge Cloud”; 4) understanding the techno-economic impacts of the vision and 5GOS, and the most effective strategies to exploit it
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Grassi, Giulio. "Connected cars : a networking challenge and a computing resource for smart cities." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066554/document.
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Récemment, les villes sont devenues "de plus en plus intelligentes", avec une multitude de périphériques IoT et de capteurs déployés partout. Parmi ces objets intelligents, les voitures peuvent jouer un rôle important. Les véhicules sont (ou seront), en effet, équipés avec plusieurs interfaces réseau, ils ont (ou auront) des capacités de calcul et des dispositifs capables d'analyser l'environnement. Pour réaliser le concept de "connected-car" il faut un changement de modèle Internet, à partir d'une architecture centrée sur l'hôte (IP) vers un paradigme centré sur l'information, comment l'architecture ICN (Information Centric Networking). Cette thèse analyse ainsi les avantages et les défis du paradigme ICN, en particulier du Named Data Networking (NDN), dans le domaine VANET, en présentant la première implémentation de NDN pour VANET (V-NDN). Il propose ensuite Navigo, un mécanisme de forwarding basé sur NDN pour la récupération de contenu en utilisant les communications V2V et V2I. Ensuite, le problème de la mobilité des fournisseurs de données est traité, proposant une solution distribuée basée sur NDN, MAP-Me. Toutefois, le rôle du véhicule dans les villes intelligentes ne s'arrête pas au niveau de la connectivité. Les voitures, avec leurs nouvelles capacités de calcul, sont les candidates idéales pour jouer un rôle dans l'architecture Fog Computing, en déplaçant des tâches de calcul vers l'edge du réseau. En tant que preuve de concept, cette thèse présente ParkMaster, un système qui combine les techniques de machine learning, le cloud et l'edge pour analyser l'environnement et traiter le problème de la disponibilité du stationnementIn the recent years we have seen a continuous integration of technology with the urban environment. This fusion aims to improve the efficiency and the quality of living in big urban agglomerates, while reducing the costs for their management. Cities are getting “smarter and smarter”, with a plethora of IoT devices and sensors deployed all over the urban areas. Among those intelligent objects, an important role may be played by cars. Modern vehicles are (or will be) indeed equipped with multiple network interfaces, they have (or will have) computational capabilities and devices able to sense the environment. However, smart and connected cars do not represent only an opportunity, but also a challenge. Computation capabilities are limited, mobility and the diversity of network interfaces are obstacles when providing connectivity to the Internet and to other vehicles. When addressing the networking aspect, we believe that a shift in the Internet model is needed, from a host oriented architecture (IP) to a more content focused paradigm, the Information Centric Networking (ICN) architectures. This thesis thus analyzes the benefits and the challenges of the ICN paradigm, in particular of Named Data Networking (NDN), in the VANET domain, presenting the first implementation running on real cars of NDN for VANET (V-NDN). It then proposes Navigo, an NDN based forwarding mechanism for content retrieval over V2V and V2I communications, with the goal of efficiently discovering and retrieving data while reducing the network overhead. Networking mobility is not only a challenge for vehicles, but for any connected mobile device. For this reason, this thesis extends its initial area of interest — VANET — and addresses the network mobility problem for generic mobile nodes, proposing a NDN-based solution, dubbed MAP–Me. MAP-Me tackles the intra-AS content provider mobility problem without relying on any fixed node in the network. It exploits notifications messages at the time of a handover and the forwarding plane to maintain the data provider “always” reachable.Finally, the “connected car” concept is not the only novel element in modern vehicles. Cars indeed won’t be only connected, but also smart, able to locally process data produced by in-car sensors. Vehicles are the perfect candidates to play an important role in the recently proposed Fog Computing architecture. Such an architecture moves computational tasks typical of the cloud away from it and brings them to the edge, closer to where the data is produced. To prove that such a model, with the car as computing edge node, is already feasible with the current technology and not only a vision for the future, this thesis presents ParkMaster. Parkmaster is a fully deployed edge-based system that combines vision and machine learning techniques, the edge (driver’s smartphone) and the cloud to sense the environment and tackle the parking availability problem
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Badokhon, Alaa. "An Adaptable, Fog-Computing Machine-to-Machine Internet of Things Communication Framework." Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1492450137643915.
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Chirindo, Tasimba Denford David. "An open vendor agnostic fog computing framework for mission critical and data dense applications." Master's thesis, Faculty of Engineering and the Built Environment, 2018. http://hdl.handle.net/11427/29984.
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Digital innovation from the Internet of Things (IoT), Artificial Intelligence, Tactile Internet and Industry 4.0 applications is transforming the way we work, commute, shop and play. Current deployment strategies of these applications emphasize mandatory cloud connectivity. However, this is not feasible in many real-world situations particularly where data dense and mission critical applications with stringent requirements are concerned. Cloud computing offers unlimited on-demand computing, storage and networking power for industry to leverage. However, as its scope and scale continues to expand, its limitations like high latency, accessibility, security and compliance shortcomings prevent its greater use and applicability particularly in scenarios where real-time communication and the quality of rapid computing delivered is a necessity. Fog computing hopes to bridge this gap by introducing an intermediary computing layer between end users and the cloud. At present, architectures for fog computing exist in specialized areas with current implementations being proprietary, vendor-locked and requiring dramatic and non-transferable changes to hardware and software to meet vendor requirements. Moreover, fog computing is still quite a recent area which makes the state of the art incipient regarding architecture definitions, middleware and real-world implementations. There is therefore an urgent need for standardization of these technologies. This is of paramount importance as otherwise, there will exist multiple and not necessarily compatible solutions which could lead to a fragmented marketplace that would fail to grow. In an effort to address these limitations in current fog architectures, this dissertation proposes and implements a novel fog computing architecture that aligns the reference architectures from a leading industry consortium, OpenFog, and a leading standards setting organization, the European Telecommunications Standards Institute (ETSI). This cooperation framework from industry, academia and regulatory institute aims to make it easier for both application developers and infrastructure solution providers to develop towards a common, open and interoperable fog computing environment. The proposed framework has the following attributes: modular, plug-in design, generic, open, standards compliant, vendor agnostic and runs on high volume standard hardware whilst preserving the benefits offered by public clouds such as containerization, virtualization, orchestration, manageability and efficiency. Moreover, for the various stakeholders in the fog value chain where it is key to strike a balance between information technology and business operations, this thesis tenders insights and best practices to help achieve these multiple and sometimes competing goals. The proposed framework was implemented in a testbed environment made up entirely of free and open source software, therefore creating a convenient point of departure for further research by others. Two geographically distributed fog node data centres and a cloud management and orchestration tool were setup in the testbed. While this evaluation framework and practical implementation demonstrated proof of concept, further evaluations were conducted to benchmark the performance against existing alternative solutions. These evaluations were based on a prototype industrial IoT application that was deployed on the testbed to evaluate the impact of the Open Vendor Agnostic Fog Framework (OVAFF) solution on application performance. The implementation showed that the proposed OVAFF solution is feasible, implementable and supports distributed edge cloud data centres. Results from the prototype application showed that OVAFF can extremely provide up to tenfold throughput and ultra-low latency, jitter and packet loss rate better than the remote clouds. Moreover, there is more superiority exhibited by the OVAFF for other non-performance based attributes like data reduction, compliance and geographical locality of control. In addition, the results also pointed towards the viability of open business models like federated infrastructure sharing and a fog market place in the fog ecosystem. Finally, this thesis tackled the highlighted open challenges in current fog systems such as orchestration, distribution, tiering, heterogeneity and resilience; which were outlined in the research motivation and problem definition.
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Svensson, Wictor. "A comparison between database and Internet of Thing solutions : For remote measuring of radon." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-34047.
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More and more devices around us are connected to the internet and communicate to each other. This includes devices such as radon sensors. Radon is a radio active gas and is the cause of several hundred cases of lung cancer. Smart connected radon sensors can be helpful to reduce the levels of radon as they provide remote access to the user. This study examines the opportunity to connect an already existing radon sensor to the “Internet of Things”. The aim of this study has been to answer the problem “find a better solution for the IoT system and develop it”. The study was performed with a literature study of three Internet of Things platforms. This resulted in one Internet of Thing platform being used throughout the study. A database system and a system with the chosen platform was implemented and a time measurement of the different systems was performed. The study has shown that a less secured system is faster and it is also shown that the Amazon Web Service IoT Core is fast with respect to the many features offered. The study concludes that the choice of system depends on where and how the system is supposed to be implement. If the system just needs to send and store data, a regular MySQL database is enough. If the system in the future is supposed to be able to communicate with other devices, a IoT platform should be used.
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Imine, Youcef. "Cloud computing security." Thesis, Compiègne, 2019. http://www.theses.fr/2019COMP2520.
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Ces dernières années, nous assistons à une immense révolution numérique de l’internet où de nombreuses applications, innovantes telles que l’internet des objets, les voitures autonomes, etc., ont émergé. Par conséquent, l’adoption des technologies d’externalisations des données, telles que le cloud ou le fog computing, afin de gérer cette expansion technologique semble inévitable. Cependant, l’utilisation du cloud ou du fog computing en tant que plateforme d’externalisation pour le stockage ou le partage des données crée plusieurs défis scientifiques. En effet, externaliser ses données signifie que l’utilisateur perd le contrôle sur ces derniers. D’où la sécurité des données devienne une préoccupation majeure qui doit être proprement traitée. C’est dans ce contexte que s’inscrivent les travaux de cette thèse dans laquelle nous avons déterminé dans un premier temps les principaux problèmes de sécurité liés à l’adoption du cloud et du fog computing. Puis, nous avons adressé trois problématiques de sécurité majeure, qui sont : 1 - Le contrôle d’accès aux données dans une architecture de type Cloud storage, où nous avons proposé une nouvelle solution de contrôle d’accès basée sur le chiffrement à base d’attributs. Notre solution assure un contrôle d’accès souple et à grains fins. De plus, elle permet d’effectuer une révocation immédiate des utilisateurs et des attributs sans aucune mise à jour des clés de chiffrement fournies aux utilisateurs. 2 - Le problème de l’authentification mutuelle entre les utilisateurs et les serveurs Fog dans une architecture Fog computing, où nous avons proposé un nouveau schéma d’authentification efficace, qui assure l’authentification mutuelle et qui est robuste contre les comportements malicieux des serveurs Fog. 3 - Le problème de traçabilité et de la protection de la vie privée dans le cadre des applications de partage d’informations publiques, où nous avons proposé une nouvelle solution pour le partage d’informations publiques assurant le service de traçabilité tout en préservant les informations privées des utilisateurs. Avec notre solution, les serveurs d’externalisations authentifient les utilisateurs sans pouvoir obtenir des informations sur leur vie privée. En cas de comportements malicieux, notre solution permet de tracer les utilisateurs malveillants grâce à une autoritéThese last years, we are witnessing a real digital revolution of Internet where many innovative applications such as Internet of Things, autonomous cars, etc., have emerged. Consequently, adopting externalization technologies such as cloud and fog computing to handle this technological expansion seems to be an inevitable outcome. However, using the cloud or fog computing as a data repository opens many challenges in prospect. This thesis addresses security issues in cloud and fog computing which is a major challenge that need to be appropriately overcomed. Indeed, adopting these technologies means that the users lose control over their own data, which exposes it to several security threats. Therefore, we first investigated the main security issues facing the adoption of cloud and fog computing technologies. As one of the main challenges pointed in our investigation, access control is indeed a cornerstone of data security. An efficient access control mechanism must provide enforced and flexible access policies that ensure data protection, even from the service provider. Hence, we proposed a novel secure and efficient attribute based access control scheme for cloud data-storage applications. Our solution ensures flexible and fine-grained access control and prevents security degradations. Moreover, it performs immediate users and attributes revocation without any key regeneration. Authentication service in fog computing architecture is another issue that we have addressed in this thesis. Some traditional authentication schemes endure latency issues while others do not satisfy fog computing requirements such as mutual authentication between end-devices and fog servers. Thus, we have proposed a new, secure and efficient authentication scheme that ensures mutual authentication at the edge of the network and remedies to fog servers' misbehaviors.Finally, we tackled accountability and privacy-preserving challenges in information-sharing applications for which several proposals in the literature have treated privacy issues, but few of them have considered accountability service. Therefore, we have proposed a novel accountable privacy preserving solution for public information sharing in data externalization platforms. Externalization servers in our scheme authenticate any user in the system without violating its privacy. In case of misbehavior, our solution allows to trace malicious users thanks to an authority
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Nafeh, Majd. "A Fog Networking Solution for DASH-based Video Streaming." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21419/.
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The delivery of video content over the internet has surged and internet video consumption has taken over the top spot in bandwidth usage. With this boom and the improvement in the quality of videos, the need for adequate delivery and data compression pushed the world for technological advances to sustain that usage. Dynamic Adaptive Streaming over HTTP (DASH) emerged as a leading choice and the standard for the delivery of video segments that are in line and conformable to the network conditions of the end users. The cloud was able to facilitate streaming by offering the resources and the storage when needed. Nevertheless, there were still problems that needed to be addressed such as latency, distribution and energy consumption. Fog computing is suggested as the solution for these problems as it can be combined with DASH to provide a more reliable and seamless stream. The combination aims to distribute the video segments over the fog nodes, allowing for a faster delivery and an efficient system. This is evaluated through a series of simulation that measure various aspects of the system. The results illustrate the feasibility and the potential of the proposed solutions.
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Ma, Bin Bin. "Data stream mining in fog computing environment with feature selection using ensemble of swarm search algorithms." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3950659.
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Wiss, Thomas. "Evaluation of Internet of Things Communication Protocols Adapted for Secure Transmission in Fog Computing Environments." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-35298.
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A current challenge in the Internet of Things is the seeking after conceptual structures to connect the presumably billions of devices of innumerable forms and capabilities. An emerging architectural concept, the fog cloud computing, moves the seemingly unlimited computational power of the distant cloud to the edge of the network, closer to the potentially computationally limited things, effectively diminishing the experienced latency. To allow computationally-constrained devices partaking in the network they have to be relieved from the burden of constant availability and extensive computational execution. Establishing a publish/subscribe communication pattern with the utilization of the popular Internet of Things application layer protocol Constrained Application Protocol is depicted one approach of overcoming this issue. In this project, a Java based library to establish a publish/subscribe communication pattern for the Constrained Application Protocol was develop. Furthermore, efforts to build and assess prototypes of several publish/subscribe application layer protocols executed over varying common as well as secured versions of the standard and non-standard transport layer protocols were made to take advantage, evaluate, and compare the developed library. The results indicate that the standard protocol stacks represent solid candidates yet one non-standard protocol stack is the considered prime candidate which still maintains a low response time while not adding a significant amount of communication overhead.
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Naas, Mohammed Islam. "Placement des données de l'internet des objets dans une infrastructure de fog." Thesis, Brest, 2019. http://www.theses.fr/2019BRES0014/document.
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Dans les prochaines années, l’Internet des objets (IoT) constituera l’une des applications générant le plus de données. Actuellement, les données de l’IoT sont stockées dans le Cloud. Avec l’augmentation du nombre d’objets connectés, la transmission de la grande quantité de données produite vers le Cloud génèrera des goulets d’étranglement. Par conséquent, les latences seront élevées. Afin de réduire ces latences, le Fog computing a été proposé comme un paradigme étendant les services du Cloud jusqu’aux périphéries du réseau. Il consiste à utiliser tout équipement localisé dans le réseau (ex. routeur) pour faire le stockage et le traitement des données. Cependant, le Fog présente une infrastructure hétérogène. En effet, ses équipements présentent des différences de performances de calcul, de capacités de stockage et d’interconnexions réseaux.Cette hétérogénéité peut davantage augmenter la latence du service. Cela pose un problème : le mauvais choix des emplacements de stockage des données peut augmenter la latence du service. Dans cette thèse, nous proposons une solution à ce problème sous la forme de quatre contributions : 1. Une formulation du problème de placement de données de l’IoT dans le Fog comme un programme linéaire. 2. Une solution exacte pour résoudre le problème de placement de données en utilisant CPLEX, un solveur de problème linéaire. 3. Deux heuristiques basées sur le principe de “diviser pour régner” afin de réduire le temps du calcul de placement. 4. Une plate-forme expérimentale pour évaluer des solutions de placement de données de l’IoT dans le Fog, en intégrant la gestion du placement de données à iFogSim, un simulateur d’environnement Fog et IoTIn the coming years, Internet of Things (IoT) will be one of the applications generating the most data. Nowadays, IoT data is stored in the Cloud. As the number of connected objects increases, transmitting the large amount of produced data to the Cloud will create bottlenecks. As a result, latencies will be high and unpredictable. In order to reduce these latencies, Fog computing has been proposed as a paradigm extending Cloud services to the edge of the network. It consists of using any equipment located in the network (e.g. router) to store and process data. Therefore, the Fog presents a heterogeneous infrastructure. Indeed, its components have differences in computing performance, storage capacity and network interconnections. This heterogeneity can further increase the latency of the service. This raises a problem: the wrong choice of data storage locations can increase the latency of the service. In this thesis, we propose a solution to this problem in the form of four contributions: 1. A formulation of the IoT data placement problem in the Fog as a linear program. 2. An exact solution to solve the data placement problem using the CPLEX, a mixed linear problem solver. 3. Two heuristics based on the principle of “divide and conquer” to reduce the time of placement computation. 4. An experimental platform for testing and evaluating solutions for IoT data placement in the Fog, integrating data placement management with iFogSim, a Fog and IoT environment simulator
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Grassi, Giulio. "Connected cars : a networking challenge and a computing resource for smart cities." Electronic Thesis or Diss., Paris 6, 2017. http://www.theses.fr/2017PA066554.
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Récemment, les villes sont devenues "de plus en plus intelligentes", avec une multitude de périphériques IoT et de capteurs déployés partout. Parmi ces objets intelligents, les voitures peuvent jouer un rôle important. Les véhicules sont (ou seront), en effet, équipés avec plusieurs interfaces réseau, ils ont (ou auront) des capacités de calcul et des dispositifs capables d'analyser l'environnement. Pour réaliser le concept de "connected-car" il faut un changement de modèle Internet, à partir d'une architecture centrée sur l'hôte (IP) vers un paradigme centré sur l'information, comment l'architecture ICN (Information Centric Networking). Cette thèse analyse ainsi les avantages et les défis du paradigme ICN, en particulier du Named Data Networking (NDN), dans le domaine VANET, en présentant la première implémentation de NDN pour VANET (V-NDN). Il propose ensuite Navigo, un mécanisme de forwarding basé sur NDN pour la récupération de contenu en utilisant les communications V2V et V2I. Ensuite, le problème de la mobilité des fournisseurs de données est traité, proposant une solution distribuée basée sur NDN, MAP-Me. Toutefois, le rôle du véhicule dans les villes intelligentes ne s'arrête pas au niveau de la connectivité. Les voitures, avec leurs nouvelles capacités de calcul, sont les candidates idéales pour jouer un rôle dans l'architecture Fog Computing, en déplaçant des tâches de calcul vers l'edge du réseau. En tant que preuve de concept, cette thèse présente ParkMaster, un système qui combine les techniques de machine learning, le cloud et l'edge pour analyser l'environnement et traiter le problème de la disponibilité du stationnementIn the recent years we have seen a continuous integration of technology with the urban environment. This fusion aims to improve the efficiency and the quality of living in big urban agglomerates, while reducing the costs for their management. Cities are getting “smarter and smarter”, with a plethora of IoT devices and sensors deployed all over the urban areas. Among those intelligent objects, an important role may be played by cars. Modern vehicles are (or will be) indeed equipped with multiple network interfaces, they have (or will have) computational capabilities and devices able to sense the environment. However, smart and connected cars do not represent only an opportunity, but also a challenge. Computation capabilities are limited, mobility and the diversity of network interfaces are obstacles when providing connectivity to the Internet and to other vehicles. When addressing the networking aspect, we believe that a shift in the Internet model is needed, from a host oriented architecture (IP) to a more content focused paradigm, the Information Centric Networking (ICN) architectures. This thesis thus analyzes the benefits and the challenges of the ICN paradigm, in particular of Named Data Networking (NDN), in the VANET domain, presenting the first implementation running on real cars of NDN for VANET (V-NDN). It then proposes Navigo, an NDN based forwarding mechanism for content retrieval over V2V and V2I communications, with the goal of efficiently discovering and retrieving data while reducing the network overhead. Networking mobility is not only a challenge for vehicles, but for any connected mobile device. For this reason, this thesis extends its initial area of interest — VANET — and addresses the network mobility problem for generic mobile nodes, proposing a NDN-based solution, dubbed MAP–Me. MAP-Me tackles the intra-AS content provider mobility problem without relying on any fixed node in the network. It exploits notifications messages at the time of a handover and the forwarding plane to maintain the data provider “always” reachable.Finally, the “connected car” concept is not the only novel element in modern vehicles. Cars indeed won’t be only connected, but also smart, able to locally process data produced by in-car sensors. Vehicles are the perfect candidates to play an important role in the recently proposed Fog Computing architecture. Such an architecture moves computational tasks typical of the cloud away from it and brings them to the edge, closer to where the data is produced. To prove that such a model, with the car as computing edge node, is already feasible with the current technology and not only a vision for the future, this thesis presents ParkMaster. Parkmaster is a fully deployed edge-based system that combines vision and machine learning techniques, the edge (driver’s smartphone) and the cloud to sense the environment and tackle the parking availability problem
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Birhanie, Habtamu. "Resource Allocation in Vehicular Fog Computing for an Optimal Use of EVs Electric Vehicles Energy." Thesis, Bourgogne Franche-Comté, 2019. http://www.theses.fr/2019UBFCK042.
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Résumé : Les progrès technologiques ont permis aux véhicules électriques d’avoir des capacités à la fois de calcul, de communication, de stockage et de perception. Néanmoins, la plupart du temps, ces véhicules électriques sont en stationnement, ce qui engendre une sous utilisation de leurs capacités embarquées. Ainsi, une meilleure gestion et une mise en commun de ces ressources sous-utilisées deviennent fortement recommandées. Les ressources agrégées seraient utiles pour des applications de sécurité routière, des applications liées au confort ou pourraient même être utilisées en tant que centre de calcul distribué. En outre, les véhicules en stationnement pourraient également être utilisés comme plate-forme de fourniture de services. Par conséquent, l’utilisation de ressources abondantes agrégées pour le déploiement de différentes applications mobiles locales a conduit au développement du concept d’informatique en brouillard véhiculaire (an anglais, Vehicular Fog Computing - VFC). Grâce à ce dernier, les véhicules dans les aires de stationnement, les centres commerciaux ou les aéroports vont agir en tant que nœuds fog. Dans un autre contexte, les applications mobiles sont devenues de plus en plus populaires, complexes et gourmandes en ressources. Certaines applications mobiles nécessitent des capacités de calcul intensives et une consommation d'énergie élevée qui transcendent les capacités limitées des appareils mobiles. Tout au long de ce travail, nous abordons les verrous liés au déploiement efficace d’un système VFC agrégeant les ressources inutilisées des véhicules électriques en stationnement pour être utilisées comme nœuds fogs répondants aux demandes de calcul des utilisateurs mobiles à proximité. Notre travail commence par un état de l'art sur les véhicules électriques et l'allocation de ressources dans le système VFC. En outre, nous évaluons le potentiel des ressources agrégées dans les véhicules électriques pour répondre aux demandes d'applications d'utilisateurs mobiles locaux en prenant en compte l'état de santé de la batterie (en anglais, State of Health - SOH) et son état de charge (en anglais, State of Charge - SOC). Notre objectif est de choisir des VEs ayant un état de santé et de charge satisfaisants pour faire partie du VFC tout en permettant aux propriétaires de ces véhicules de disposer d’une quantité d’énergie suffisante pour leur mobilité. Nous abordons, par la suite, le problème d’allocation de ressources avec une nouvelle solution basée sur le processus de décision Markovien (en anglais, Markov Decision Process - MDP) qui vise à optimiser l’utilisation de l’énergie des véhicules électriques pour répondre à la fois à aux demandes de calcul et de mobilité des utilisateurs. Enfin, nous proposons une approche basée sur un jeu stochastique pour montrer la dynamique de la demande de calcul des utilisateurs mobiles et la disponibilité des ressources des véhicules électriquesAbstract: Technological advancements made it possible for Electric vehicles (EVs) to have onboard computation, communication, storage, and sensing capabilities. Nevertheless, most of the time these EVs spend their time in parking lots, which makes onboard devices cruelly underutilized. Thus, a better management and pooling these underutilized resources together would be strongly recommended. The new aggregated resources would be useful for traffic safety applications, comfort related applications or can be used as a distributed data center. Moreover, parked vehicles might also be used as a service delivery platform to serve users. Therefore, the use of aggregated abundant resources for the deployment of different local mobile applications leads to the development of a new architecture called Vehicular Fog Computing (VFC). Through VFC, abundant resources of vehicles in the parking area, on the mall or in the airport, can act as fog nodes. In another context, mobile applications have become more popular, complex and resource intensive. Some sophisticated embedded applications require intensive computation capabilities and high-energy consumption that transcend the limited capabilities of mobile devices. Throughout this work, we tackle the problem of achieving an effective deployment of a VFC system by aggregating unused resources of parked EVs, which would be eventually used as fog nodes to serve nearby mobile users’ computation demands. At first, we present a state of the art on EVs and resource allocation in VFC. In addition, we assess the potential of aggregated resources in EVs for serving local mobile users’ applications demands by considering the battery State of Health (SOH) and State of Charge (SOC). Here, the objective is to choose EVs with a good condition of SOH and SOC so that owners secure tolerable amount of energy for mobility. Then, we address the problem of resource allocation scheme with a new solution based on Markov Decision Process (MDP) that aims to optimize the use of EVs energy for both computing users’ demands and mobility. Hence, the novelty of this contribution is to take into consideration the amount of aggregated EVs resource for serving users’ demands. Finally, we propose a stochastic theoretical game approach to show the dynamics of both mobile users’ computation demands and the availability of EVs resources
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Gottardelli, Chiara <1991>. "FOG COMPUTING: THE KEYSTONE FOR THE FUTURE OF INDUSTRIAL IoT. IMPACTS ON LEAN PRODUCTION ENVIRONMENTS." Master's Degree Thesis, Università Ca' Foscari Venezia, 2018. http://hdl.handle.net/10579/13667.
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The Fourth Industrial revolution dominates the current discussion of researchers on manufacturing.
At the same time, worldwide companies are becoming aware of the importance of Industrial IoT (IIoT) for competitive advantages.
Even Governments have assumed an important role in the field and set themselves as promoters of technological change with policies in favor of industrial digitalization.
In this scenario, Industrial IoT is driving the need for extensive adoption of advanced IT features across multiple Industry verticals. Moreover, in companies that apply Lean production concepts, IIoT accelerates Lean benefits.
The research gives an overview over existing combination of Industry 4.0 and Lean production, through Fog computing technology.
Fog computing brings many Cloud IT features close to industrial processes and merges those with real-time features, increasing production efficiency.
Fog Computing was introduced by Cisco in 2014 and a startup located in Silicon Valley, Nebbiolo Technologies, was the first pioneer on developing this new technology.
This company is deploying it in different industrial applications.
Considering the industrial automation, this thesis wants to underline the improvements and changes within corporate organizational structure resulting from the application of Fog computing.
Furthermore, this paper wants to validate the quantitative and qualitative data from two case studies deployed in worldwide companies: one in food industry and the other in the cosmetic and pharmaceutical sector.
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Muhammad, Jan. "Application Deployment in Relay Based Edge Computing Scenarios." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20049/.
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Fog computing is a developing model as an innovative approach to increase the capacity of the cloud computing platform, which has been proposed to expand the Internet of Things (IoT) task to the edge of the network. Fog computing and edge computing are similar; both of them are promised to maximize the computing capabilities inside the local network to accomplish the computational responsibilities. Both computing mechanics can support systems to reduce their dependence on cloud-based platform to examine data, which usually directs to latency problems. The IoT brings to an ever-widening existence of ubiquitous networking devices in business, private and public areas. These networked computing devices feature storage, computational, and networking resources, instead of simply acting as a sensor. It is positioned at the edge of the network so that these resources can be used to execute the IoT applications in a distributed way. This idea is known as fog computing. We intensely propose relevant fog computing architecture.
Genetic Algorithm contributes the general framework for solving complicated problems as a kind of heuristic algorithm and this optimization technique is inspired by natural evolution. We work in this project concerning the application deployment for the IoT applications over fog resources as an optimization problem.
We propose three edge computing scenarios (centralized, distributed and random) with a relay in this work, so that the application execution can achieve the maximum probability, when these edge computing scenarios are used with a relay. Our numerical results illustrates that the with the relay based edge computing scenarios, we increase the probability of coverage and it shows that our work is successful.
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Singh, Navjot. "Planning of Mobile Edge Computing Resources in 5G Based on Uplink Energy Efficiency." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38444.
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Increasing number of devices demand for low latency and high-speed data transmission require that the computation resources to be closer to users. The emerging Mobile Edge Computing (MEC) technology aims to bring the advantages of cloud computing which are computation, storage and networking capabilities in close proximity of user. MEC servers are also integrated with cloud servers which give them flexibility of reaching vast computational power whenever needed. In this thesis, leveraging the idea of Mobile Edge Computing, we propose algorithms for cost-efficient and energy-efficient the placement of Mobile Edge nodes. We focus on uplink energy-efficiency which is essential for certain applications including augmented reality and connected vehicles, as well as extending battery life of user equipment that is favorable for all applications. The experimental results show that our proposed schemes significantly reduce the uplink energy of devices and minimizes the number of edge nodes required in the network.
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Marini, Riccardo. "Software Defined Networking Architectures for LoRaWAN." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.
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This thesis proposes new solutions for LoRaWAN networks taking advantages of Software Defined Networking architectures. In particular, an analysis of the current implementation of the Adaptive Data Rate mechanism developed by LoRaWAN standard, as well as a proposal of a new algorithm, will be provided. This will be addressed by considering both a cloud-based and a fog-based architecture in order to observe differences between the two approaches in a number of different scenarios. The proposed algorithms and the two architectures are compared via numerical results achieved through simulations and experimental tests.