Relevant bibliographies by topics / Fog systems

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  2. Dissertations / Theses
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Academic literature on the topic 'Fog systems'

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Published: 10 May 2025

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Journal articles on the topic "Fog systems"

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Phan, Linh-An, Duc-Thang Nguyen, Meonghun Lee, Dae-Heon Park, and Taehong Kim. "Dynamic fog-to-fog offloading in SDN-based fog computing systems." Future Generation Computer Systems 117 (April 2021): 486–97. http://dx.doi.org/10.1016/j.future.2020.12.021.

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Sandvik, Jens-Petter, Katrin Franke, Habtamu Abie, and André Årnes. "Evidence in the fog – Triage in fog computing systems." Forensic Science International: Digital Investigation 44 (March 2023): 301506. http://dx.doi.org/10.1016/j.fsidi.2023.301506.

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Benila S, Benila S., and Usha Bhanu N. Benila S. "Fog Managed Data Model for IoT based Healthcare Systems." 網際網路技術學刊 23, no. 2 (March 2022): 217–26. http://dx.doi.org/10.53106/160792642022032302003.

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<p>In Internet of things enabled healthcare system, sensors create vast volumes of data that are analyzed in the cloud. Transferring data from the cloud to the application takes a long time. An effective infrastructure can reduce latency and costs by processing data in real-time and close to the user devices. Fog computing can solve this issue by reducing latency by storing, processing, and analyzing patient data at the network edge. Placing the resources at fog layer and scheduling tasks is quite challenging in Fog computing. This paper proposes a Fog Managed Data Model (FMDM) with three layers namely Sensor, Fog and cloud to solve the aforementioned issue. Sensors generate patient data and that are managed and processed by Fog and cloud layers. Tasks are scheduled using a Weighted Fog Priority Job Scheduling algorithm (WFPJS) and fog nodes are allocated based on Priority based Virtual Machine Classification Algorithm (PVCA). The performance of this model is validated with static scheduling techniques with variable patient counts and network configurations. The proposed FMDM with WFPJS reduces response time, total execution cost, network usage, network latency, computational latency and energy consumption.</p> <p>&nbsp;</p>
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Zhurylo, Oleh, and Oleksii Liashenko. "Architecture and iot security systems based on fog computing." INNOVATIVE TECHNOLOGIES AND SCIENTIFIC SOLUTIONS FOR INDUSTRIES, no. 1 (27) (July 2, 2024): 54–66. http://dx.doi.org/10.30837/itssi.2024.27.054.

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The subject of the study is is the security architecture of the Internet of Things (IoT) based on fog computing, which allows providing efficient and secure services for many IoT users. The goal is to investigate the security architecture for IoT systems based on fog computing. To achieve the goal, the following tasks were solved: the concept of fog computing is proposed, its architecture is considered and a comparative analysis of fog and cloud computing architectures is made; the principles of designing and implementing the architecture of a fog computing system are outlined; multi-level security measures based on fog computing are investigated; and the areas of use of fog computing-based Internet of Things networks are described. When performing the tasks, such research methods were used as: theoretical analysis of literature sources; analysis of the principles of designing and implementing the security architecture of the Internet of Things; analysis of security measures at different levels of the architecture. The following results were obtained: the architecture of fog computing is considered and compared with the cloud architecture; the principles of designing and implementing the architecture of fog computing systems are formulated; multi-level IoT security measures based on fog computing are proposed. Conclusions: research on IoT security systems based on fog computing has important theoretical implications. The fog computing architecture, in contrast to the cloud architecture, better meets the demand for high traffic and low latency of mobile applications, providing more advantages for systems that require real-time information processing. When designing and implementing the architecture of fog computing systems, the factors of memory capacity, latency, and utility should be taken into account to effectively integrate fog technologies with IoT. To ensure a high level of system security, multi-level security measures should be implemented using both software and hardware solutions.
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Pinche, Cristobal, and Loren Ruiz. "Fog on the brine — Fog-catching systems for arid lands." Waterlines 14, no. 4 (April 1996): 4–7. http://dx.doi.org/10.3362/0262-8104.1996.013.

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Alenizi, Faten, and Omer Rana. "Dynamically Controlling Offloading Thresholds in Fog Systems." Sensors 21, no. 7 (April 3, 2021): 2512. http://dx.doi.org/10.3390/s21072512.

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Fog computing is a potential solution to overcome the shortcomings of cloud-based processing of IoT tasks. These drawbacks can include high latency, location awareness, and security—attributed to the distance between IoT devices and cloud-hosted servers. Although fog computing has evolved as a solution to address these challenges, it is known for having limited resources that need to be effectively utilized, or its advantages could be lost. Computational offloading and resource management are critical to be able to benefit from fog computing systems. We introduce a dynamic, online, offloading scheme that involves the execution of delay-sensitive tasks. This paper proposes an architecture of a fog node able to adjust its offloading threshold dynamically (i.e., the criteria by which a fog node decides whether tasks should be offloaded rather than executed locally) using two algorithms: dynamic task scheduling (DTS) and dynamic energy control (DEC). These algorithms seek to minimize overall delay, maximize throughput, and minimize energy consumption at the fog layer. Compared to other benchmarks, our approach could reduce latency by up to 95%, improve throughput by 71%, and reduce energy consumption by up to 67% in fog nodes.
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Almulifi, Asma, and Heba Kurdi. "The Role of Fog Device Density in IoT-Fog-Cloud Systems." Procedia Computer Science 241 (2024): 242–47. http://dx.doi.org/10.1016/j.procs.2024.08.033.

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Marir, Souad, Faiza Belala, and Nabil Hameurlain. "A Strategy-Based Formal Approach for Fog Systems Analysis." Future Internet 14, no. 2 (February 9, 2022): 52. http://dx.doi.org/10.3390/fi14020052.

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Fog systems are a new emergent technology having a wide range of architectures and pronounced needs making their design complex. Consequently, the design of fog systems is crucial, including service portability and interoperability between the various elements of a system being the most essential aspects of fog computing. This article presents a fog system cross-layer architecture as a first step of such a design to provide a graphical and conceptual description. Then, a BiAgents* (Bigraphical Agents) formal model is defined to provide a rigorous description of physical, virtual, and behavioural aspects of Fog systems. Besides, this formalisation is implemented and executed under a Maude strategy system. The proposed approach is illustrated through a case study: an airport terminal Luggage Inspection System (LIS) while checking the correctness of its relevant properties: the portability of data and their interoperability. The integration of the Maude strategies in the rewriting of Fog system states made it possible to guide the execution of the model and its analysis.
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Li, Xuewei, Yuchen Jia, Yufei Chen, Guanyang Xing, Xiaohua Zhao, and Jian Rong. "Safety Evaluation of Fog Warning Systems in a Connected Vehicle Environment Based on Sample Entropy." Journal of Advanced Transportation 2021 (October 6, 2021): 1–15. http://dx.doi.org/10.1155/2021/3047756.

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Changes in driving behavior caused by reduced visibility in fog can lead to crashes. To improve driving safety in fog weather, a fog warning system based on connected vehicle (CV) technology is proposed. From the perspective of human factors, this study evaluates the driving safety based on drivers’ speed change under different fog levels (i.e., no fog, light fog, and heavy fog) and different technical levels (i.e., normal, with a dynamic message sign (DMS), and with a human-machine interface (HMI)). The driving behavior data were collected by a driving simulation experiment. The experimental road was divided into three zones: clear zone, transition zone, and fog zone. To quantify the change of vehicle speed comprehensively, the speed and acceleration were selected. Meanwhile, the vehicle speed safety entropy and acceleration safety entropy were proposed based on sample entropy theory. Furthermore, the changes of each index in different zones were analyzed. The results show that the use of fog warning system can improve speed stability and driving safety in fog zones and can make the driver decelerate in advance with a smaller deceleration before entering the fog zones. The higher the technical level is, the earlier the driver decelerates. Under the condition of light fog, the fog warning system with HMI has a better effect in terms of improving speed stability, while under the condition of heavy fog, there is little difference between the two technical levels. In general, this study proposed a novel safety evaluation index and a general evaluation method of the fog warning system.
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Hegarty, R., and M. Taylor. "Digital evidence in fog computing systems." Computer Law & Security Review 41 (July 2021): 105576. http://dx.doi.org/10.1016/j.clsr.2021.105576.

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Dissertations / Theses on the topic "Fog systems"

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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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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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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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Ismahil, Dlovan. "Investigating Fog- and Cloud-based Control Loops for Future Smart Factories." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-36705.

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In the recent years we have seen that internet connectivity has multiplied vastly and that more and more computation and information storage are moved to the cloud. Similarly to other types of networks, industrial systems also see an increase in the number of communicating devices. Introduction of wireless communication into industrial systems instead of currently used wired networks will allow interconnection of all kinds of stationary and mobile machinery, robots and sensors and thereby bring multiple benefits. Moreover, recent developments in cloud and fog computing open many new opportunities in control, analysis and maintenance of industrial systems. Wireless systems are easy to install and maintain and relocation of data analysis and control services from local controllers to the cloud can make possible computations requiring a lot of resources, improve efficiency of collaboration between different parts of a plant or several plans as cloud servers will be able to store information and be accessible from all of them. However, even though introduction of wireless communication and cloud services brings a lot of benefits, new challenges in fulfilling industrial requirements arise as, e.g., packet delivery rates might be affected by disturbances introduced in wireless channels, data storage on distant servers might introduce timing and security issues, resource allocation and reservation for controllers supervising multiple processes should be considered to provide real-time services. The main goal of this thesis work is to consider design possibilities for a factory including local and cloud controllers, i.e. look at how the work of the factory should be organized, where control decisions should be made, analyze pros and cons of making the decisions at local (fog) and cloud servers. To narrow down the problem, an example factory with who independent wireless networks (each consisting of one sensor, one actuator and one local control node) and a cloud controller controlling both of them will be considered. Selected structure allows all the questions of interest to be considered, while its prototype can be built using available for this thesis work equipment
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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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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.
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Bakhshi, Valojerdi Zeinab. "Persistent Fault-Tolerant Storage at the Fog Layer." Licentiate thesis, Mälardalens högskola, Inbyggda system, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-55680.

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Clouds are powerful computer centers that provide computing and storage facilities that can be remotely accessed. The flexibility and cost-efficiency offered by clouds have made them very popular for business and web applications. The use of clouds is now being extended to safety-critical applications such as factories. However, cloud services do not provide time predictability which creates a hassle for such time-sensitive applications. Moreover, delays in the data communication between clouds and the devices the clouds control are unpredictable. Therefore, to increase predictability an intermediate layer between devices and the cloud is introduced. This layer, the Fog layer, aims to provide computational resources closer to the edge of the network. However, the fog computing paradigm relies on resource-constrained nodes, creating new potential challenges in resource management, scalability, and reliability. Solutions such as lightweight virtualization technologies can be leveraged for solving the dichotomy between performance and reliability in fog computing. In this context, container-based virtualization is a key technology providing lightweight virtualization for cloud computing that can be applied in fog computing as well. Such container-based technologies provide fault tolerance mechanisms that improve the reliability and availability of application execution.  By the study of a robotic use-case, we have realized that persistent data storage for stateful applications at the fog layer is particularly important. In addition, we identified the need to enhance the current container orchestration solution to fit fog applications executing in container-based architectures. In this thesis, we identify open challenges in achieving dependable fog platforms. Among these, we focus particularly on scalable, lightweight virtualization, auto-recovery, and re-integration solutions after failures in fog applications and nodes. We implement a testbed to deploy our use-case on a container-based fog platform and investigate the fulfillment of key dependability requirements. We enhance the architecture and identify the lack of persistent storage for stateful applications as an important impediment for the execution of control applications. We propose a solution for persistent fault-tolerant storage at the fog layer, which dissociates storage from applications to reduce application load and separates the concern of distributed storage. Our solution includes a replicated data structure supported by a consensus protocol that ensures distributed data consistency and fault tolerance in case of node failures. Finally, we use the UPPAAL verification tool to model and verify the fault tolerance and consistency of our solution.
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Nan, Yucen. "Cost-effective Offloading Strategy for Delay-sensitive Applications in Cloud of Things Systems." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/16789.

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The steep rise of Internet of Things (IoT) applications along with the limitations of Cloud Computing to address all IoT requirements leveraged a new distributed computing paradigm called Fog Computing, which aims to process data at the edge of the network. With the help of Fog Computing, some of the uncertainties of the communication among different tiers like the transmission latency, monetary spending and application loss caused by Cloud Computing can be effectively reduced. However, as the processing capacity of Fog nodes is more limited than that of cloud platforms, running all applications indiscriminately on these nodes can cause some QoS requirement to be violated. Therefore, we apply Three-tier Cloud of Things Systems (including Things Tier, Fog Tier and Cloud Tier), a simple yet powerful model of IoT to do the applications offloading between Fog Tier and Cloud Tier to guarantee some processing requirements. And there is important decision-making as to where executing each application in order to produce a cost effective solution and fully meet application requirements. This thesis makes the original contribution of an appropriate dynamical optimization about the application offloading. We call this the study of online decision making and this study is based on queueing theory. Additionally, we clarify the relationship between processing time and QoS requirements (like the money cost) to provide cost-effective application processing service. In particular, we are interested in the tradeoff in terms of average response time, average cost and average number of application loss. In this thesis, we present an online algorithm, called Unit-slot Optimization, based on the technique of Lyapunov Optimization. The Unit-slot Optimization is a quantified near-optimal online solution to balance the two-way tradeoff between average response time and average cost. Meanwhile, the proposed optimization is satisfied with the three-way tradeoff among average response time, average cost and average number of application loss as well. After that, we evaluate the performance of the Unit-slot Optimization algorithm by a number of experiments. The experimental results not only match up the theoretical analyses properly, but also demonstrate that our proposed algorithm can successfully provide cost-effective processing, while guaranteeing average response time in a Three-tier Cloud of Things System.
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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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Awad, Hiba. "Quality of service assurance before deployment of fog systems with model-based engineering and DevOps." Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2025. http://www.theses.fr/2025IMTA0468.

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Le Fog Computing décentralise le Cloud en rapprochant les services de calcul, de stockage et de réseau de la périphérie du réseau. Cette approche réduit la latence, l’utilisation de la bande passante et améliore le traitement en temps réel. Cependant, la complexité et l’hétérogénéité des systèmes Fog rendent leur gestion difficile et coûteuse. Identifier les erreurs en phase d’exécution nécessite souvent de revenir aux étapes de conception, ce qui entraîne des coûts élevés en temps et en ressources. La vérification pré-déploiement est donc essentielle pour garantir fiabilité et efficacité. Les systèmes Fog, utilisés dans des domaines variés (santé, automobile, villes intelligentes), ajoutent de la complexité aux processus de vérification et de déploiement. Pour y répondre, nous proposons une approche générique et personnalisable basée sur un processus de vérification en deux étapes, combinant les phases de conception et de pré-déploiement, tout en automatisant les activités de vérification et de déploiement. Notre solution repose sur un langage de modélisation Fog adaptable, la vérification des propriétés non fonctionnelles à la conception (sécurité, énergie), et la génération de configurations de déploiement indépendantes des outils. La vérification pré-déploiement associe outils de déploiement et solutions QoS pour garantir la conformité aux critères définis avant le déploiement final. Validée par trois cas d’usage (campus intelligent, parking intelligent, hôpital intelligent), cette approche réduit les coûts, simplifie la gestion des systèmes Fog et garantit leur QoS. En intégrant des pratiques DevOps, elle répond aux exigences des environnements industriels et académiques modernes
Fog Computing decentralizes the Cloud by bringing computation, storage, and network services closer to the edge. This reduces latency and bandwidth usage while improving real-time processing. However, the complexity and heterogeneity of Fog systems, often comprising diverse entities, make lifecycle management challenging and costly. Runtime error handling frequently requires revisiting earlier phases, which is both timeconsuming and expensive. Ensuring reliability through pre-deployment verification is therefore essential. Fog systems are deployed in domains such as healthcare, automotive, and smart cities, further complicating verification and deployment processes. To address these challenges, we propose a generic and customizable approach based on a two-step verification process. This approach focuses on the design-time and pre-deployment phases, automating key verification and deployment activities. Our solution features a customizable Fog modeling language, design-time verification of non-functional properties (e.g., security, energy), preparation of pre-deployment configurations, and integration with industrial DevOps tools and Quality of Service (QoS) solutions. By combining Model-Based Engineering and DevOps practices, our approach ensures QoS, reduces deployment costs, and enhances automation to tackle the complexity of Fog systems. We validated this approach using three literature-based use cases—smart campus, smart parking, and smart hospital. Results demonstrate its effectiveness in QoS verification, deployment automation, and reducing complexity and costs, highlighting its relevance to state-of-the-art engineering and DevOps practices
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Books on the topic "Fog systems"

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Yang, Yang, Xiliang Luo, Xiaoli Chu, and Ming-Tuo Zhou. Fog-Enabled Intelligent IoT Systems. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-23185-9.

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Joh, Henschel, and Desert Research Foundation of Namibia., eds. NAMFOG: Namibian application of fog-collecting systems. Walvis Bay, Namibia: Desert Research Foundation of Namibia, 1998.

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Bank, World, ed. Clearing the global health fog: A systematic review of the evidence on integration of health systems and targeted interventions. Washington, D.C: World Bank, 2009.

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1901-1972, Bertalanffy Ludwig von, Liseev I. K, and Sadovskiĭ V. N, eds. Sistemnyĭ podkhod v sovremennoĭ nauke: K 100-letii︠u︡ Li︠u︡dviga fon Bertalanfi. Moskva: Progress-Tradit︠s︡ii︠a︡, 2004.

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United States. Federal Highway Administration., ed. TECHBRIEF... HIGHWAY FOG WARNING SYSTEM... U.S. DEPARTMENT OF TRANSPORTATION. [S.l: s.n., 1999.

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Joseph, Catherine. Prospective payment system evaluation studies: Data systems. Cambridge, Massachusetts: Abt Associates, 1988.

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San Francisco (Calif.). Office of the Controller. City Services Auditor Division. Port Commission: Concession reviews of BAE Systems, San Francisco ship repair ; RGN Corporation dba Butterfly Restaurant ; Castagnola's Restaurant ; Frances Y. Chu and Jyi Jeng Hwang dba Crab Station ; Blue Jeans Equities West dba Fog City Diner ; Golden Gate Scenic Steamship Corporation ; Scoma's Restaurant, Inc. San Francisco, Calif: Office of the Controller, 2009.

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United States. Department of Health and Human Services., ed. The Metropolitan medical response system's field operations guide (FOG) for the Metropolitan Medical Strike Team. Rockville, Md: U.S. Department of Health and Human Services, 1998.

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Cox, Christopher. Essentials of UMTS. New York: Cambridge University Press, 2008.

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Nat︠s︡ionalʹnai︠a︡ assot︠s︡iat︠s︡ii︠a︡ operatorov seteĭ svi︠a︡zi tretʹego pokolenii︠a︡ (Russia). Perspektivy vnedrenii︠a︡ sistem mobilʹnoĭ svi︠a︡zi tretʹego pokolenii︠a︡ v Rossii. Moskva: Nat︠s︡ionalʹnai︠a︡ assot︠s︡iat︠s︡ii︠a︡ operatorov, 2001.

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Book chapters on the topic "Fog systems"

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Kopetz, Hermann, and Wilfried Steiner. "Cloud and Fog Computing." In Real-Time Systems, 343–65. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11992-7_14.

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Yang, Yang, Xiliang Luo, Xiaoli Chu, and Ming-Tuo Zhou. "Fog-Enabled Multi-Robot System." In Fog-Enabled Intelligent IoT Systems, 99–131. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23185-9_4.

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Yang, Yang, Xiliang Luo, Xiaoli Chu, and Ming-Tuo Zhou. "Fog-Enabled Intelligent Transportation System." In Fog-Enabled Intelligent IoT Systems, 163–84. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23185-9_6.

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Fuzzi, Sandro. "Radiation Fog Chemistry and Microphysics." In Chemistry of Multiphase Atmospheric Systems, 213–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-70627-1_8.

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Yang, Yang, Xiliang Luo, Xiaoli Chu, and Ming-Tuo Zhou. "Fog Computing Architecture and Technologies." In Fog-Enabled Intelligent IoT Systems, 39–60. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23185-9_2.

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Yang, Yang, Xiliang Luo, Xiaoli Chu, and Ming-Tuo Zhou. "Fog-Enabled Wireless Communication Networks." In Fog-Enabled Intelligent IoT Systems, 133–61. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23185-9_5.

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Rahman, Fatin Hamadah, Thien Wan Au, S. H. Shah Newaz, and Wida Susanty Haji Suhaili. "A Performance Study of High-End Fog and Fog Cluster in iFogSim." In Advances in Intelligent Systems and Computing, 87–96. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03302-6_8.

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Siddiqui, Eram Fatima, Sandeep Kumar Nayak, and Mohd Faisal. "Latency Evaluation in an IoT-Fog Model." In Intelligent Sustainable Systems, 605–13. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-6369-7_55.

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Yoshikawa, Kohei, and Shinji Sugawara. "Efficient Content Sharing Using Dynamic Fog in Cloud-Fog-Edge Three-Tiered Network." In Complex, Intelligent and Software Intensive Systems, 517–27. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08812-4_50.

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Achari, Shristi, and Rahul Johari. "FOG-EE Computing: Fog, Edge and Elastic Computing, New Age Cloud Computing Paradigms." In Advances in Intelligent Systems and Computing, 579–89. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3071-2_47.

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Conference papers on the topic "Fog systems"

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Sharmila, P., Prisha L, Dhaarani K, Sri Vidhya B, and Vishal G S. "Fog Penetration Radar." In 2024 International Conference on Power, Energy, Control and Transmission Systems (ICPECTS), 1–4. IEEE, 2024. https://doi.org/10.1109/icpects62210.2024.10780146.

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Mezaal, Ali Abdulkareem, Star Jabbar Zahab, E. A. Tawfek, Sabeeh Thamer Fadhil, Haider Alabdeli, Ali Salman, and Abdul Redha Hussein Sabr. "Coordinated Management of Fog-to-Cloud (D2C) Systems: Foggy Clouds and Clouds Fogs." In 2024 International Conference on IoT, Communication and Automation Technology (ICICAT), 478–85. IEEE, 2024. https://doi.org/10.1109/icicat62666.2024.10923169.

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Blanco, Gabriela Azucena Ayala, Emiliano Nazareno Rojas Marcelli, Alex Rubén Stockel Duarte, Hsiang-Ting Huang, Keng-Ying Li, and Tai-Lin Chin. "Deadline-Aware Task Scheduling for Cloud-Fog Systems." In 2025 28th Conference on Innovation in Clouds, Internet and Networks (ICIN), 59–63. IEEE, 2025. https://doi.org/10.1109/icin64016.2025.10942963.

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Gangrade, Priyanshi, Virendra Singh Kushwah, Saroj S. Date, Archana D. Jagdale, Kamal Upreti, and Vinai K. Singh. "Edge and Fog Computing in Cyber-Physical Systems." In 2025 International Conference on Intelligent Control, Computing and Communications (IC3), 172–76. IEEE, 2025. https://doi.org/10.1109/ic363308.2025.10956222.

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Sahu, Ritarani, Suchismita Chinara, Prabhanjan Mishra, and Shyamapada Mukherjee. "Energy and Delay Optimization for Task Offloading in IoT-Fog Environment with Homogeneous Logical Instances on Fog Devices." In 2024 12th International Conference on Intelligent Systems and Embedded Design (ISED), 1–6. IEEE, 2024. https://doi.org/10.1109/ised63599.2024.10957407.

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E, Veera Boopathy, Nathiya R, Sathish Kumar D, Sheik Arafat I, Kiruba Shankar Gajendiran, and Ramana S. "Advanced Fog and Pollution-Resistant Accident Detection System." In 2024 10th International Conference on Electrical Energy Systems (ICEES), 1–4. IEEE, 2024. https://doi.org/10.1109/icees61253.2024.10776913.

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Al-Khafajiy, Mohammed, Thar Baker, Atif Waraich, Omar Alfandi, and Aseel Hussien. "Enabling High Performance Fog Computing through Fog-2-Fog Coordination Model." In 2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA). IEEE, 2019. http://dx.doi.org/10.1109/aiccsa47632.2019.9035353.

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Matulich, Dan S. "Aircraft Fog Control Systems." In Intersociety Conference on Environmental Systems. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1986. http://dx.doi.org/10.4271/860914.

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Mohamed, Nader, Jameela Al-Jaroodi, and Imad Jawhar. "Fog-Enabled Multi-Robot Systems." In 2018 IEEE 2nd International Conference on Fog and Edge Computing (ICFEC). IEEE, 2018. http://dx.doi.org/10.1109/cfec.2018.8358727.

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Tuvakov, Jemshit, and KeeHyun Park. "On the Fog Node Model for Multi-purpose Fog Computing Systems." In 2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). IEEE, 2018. http://dx.doi.org/10.1109/iemcon.2018.8614845.

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Reports on the topic "Fog systems"

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Linker, Raphael, Murat Kacira, Avraham Arbel, Gene Giacomelli, and Chieri Kubota. Enhanced Climate Control of Semi-arid and Arid Greenhouses Equipped with Fogging Systems. United States Department of Agriculture, March 2012. http://dx.doi.org/10.32747/2012.7593383.bard.

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The main objectives were (1) to develop, implement and validate control procedures that would make it possible to maintain year-round air temperature and humidity at levels suitable for crop cultivation in greenhouses operating in arid and semi-arid regions and (2) to investigate the influence of the operational flexibility of the fogging system on the performance of the system. With respect to the development of climate controllers, we developed a new control approach according to which ventilation is used to maintain the enthalpy of the greenhouse air and fogging is used to adjust the humidity ratio inside the greenhouse. This approach is suitable mostly for greenhouses equipped with mechanized ventilation, and in which the air exchange rate can be controlled with enough confidence. The development and initial validation of the controllers were performed in a small experimental greenhouses located at the Agricultural Research Organization and very good tracking were obtained for both air temperature and relative humidity (maximum mean deviations over a 10-min period with constant setpoints lower than 2.5oC and 5% relative humidity). The robust design approach used to develop the controllers made it possible to transfer successfully these controllers to a much larger semi-commercial greenhouse located in the much drier Arava region. After only minimal adjustments, which did not require lengthy dedicated experiments, satisfactory tracking of the temperature and humidity was achieved, with standard deviation of the tracking error lower than 1oC and 5% for temperature and relative humidity, respectively. These results should help promote the acceptance of modern techniques for designing greenhouse climate controllers, especially since given the large variety of greenhouse structures (shape, size, crop system), developing high performance site-specific controllers for each greenhouse is not feasible. In parallel to this work, a new cooling control strategy, which considers the contribution of humidification and cooling from the crop, was developed for greenhouses equipped with natural ventilation. Prior to the development of the cooling strategy itself, three evapotranspiration models were compared in terms of accuracy and reliability. The cooling strategy that has been developed controls the amount of fog introduced into the greenhouse as well as the percentage of vent openings based on the desired vapor pressure deficit (VPD) and enthalpy, respectively. Numerical simulations were used to compare the performance of the new strategy with a constant fogging rate strategy based on VPD, and on average, the new strategy saved 36% water and consumed 30% less electric energy. In addition, smaller air temperature and relative humidity fluctuations were achieved when using the new strategy. Finally, it was demonstrated that dynamically varying the fog rate and properly selecting the number of nozzles, yields additional water and electricity savings.
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Jaradat, Raed, Erin Stirgus, Simon Goerger, Randy Buchanan, Niamat Ullah Ibne Hossain, Junfeng Ma, and Reuben Burch. Assessment of workforce systems preferences/skills based on employment domain. Engineer Research and Development Center (U.S.), January 2020. http://dx.doi.org/10.21079/11681/39399.

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Given the growing demand for a workforce with an understanding of system of systems, there is a need to assess an individual’s systems thinking skills. This research was undertaken to address this need by measuring an individual’s inclination to work on complex system problems based on their systems thinking score. This article investigates the correlation between employment domains and an individual’s systems thinking preferences/skills. Results of this research show that each employment domain is significantly different in their systems thinking preferences/skills profiles as well as significantly different in how the employment domains perceive change and their system’s worldview.
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London, Jonathan. Outlier Vietnam and the Problem of Embeddedness: Contributions to the Political Economy of Learning. Research on Improving Systems of Education (RISE), February 2021. http://dx.doi.org/10.35489/bsg-rise-wp_2021/062.

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Recent literature on the political economy of education highlights the role of political settlements, political commitments, and features of public governance in shaping education systems’ development and performance around learning. Vietnam’s experiences provide fertile ground for the critique and further development of this literature including, especially, its efforts to understand how features of accountability relations shape education systems’ performance across time and place. Globally, Vietnam is a contemporary outlier in education, having achieved rapid gains in enrolment and strong learning outcomes at relatively low levels of income. This paper proposes that beyond such felicitous conditions as economic growth and social historical and cultural elements that valorize education, Vietnam’s distinctive combination of Leninist political commitments to education and high levels of societal engagement in the education system often works to enhance accountability within the system in ways that contribute to the system’s coherence around learning; reflecting the sense and reality that Vietnam is a country in which education is a first national priority. Importantly, these alleged elements exist alongside other features that significantly undermine the system’s coherence and performance around learning. These include, among others, the system’s incoherent patterns of decentralization, the commercialization and commodification of schooling and learning, and corresponding patterns of systemic inequality. Taken together, these features of education in Vietnam underscore how the coherence of accountability relations that shape learning outcomes are contingent on the manner in which national and local systems are embedded within their broader social environments while also raising intriguing ideas for efforts to understand the conditions under which education systems’ performance with respect to learning can be promoted, supported, and sustained.
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London, Jonathan D., and Bich-Hang Duong. The Politics of Education and Learning in Vietnam: Contributions to a Theory of Embedded Accountabilities. Research on Improving Systems of Education (RISE), March 2023. http://dx.doi.org/10.35489/bsg-rise-2023/pe10.

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This paper locates many of the most important strengths and weaknesses in Vietnam’s education system in the politics of education and in features of the country’s education system’s societal embedding. By the politics of education, we mean the relations of power and authority and of domination, contestation, cooperation, and accommodation that shape the functioning of the education system as an institutional field. By the societal embeddedness, we refer to the system’s interdependent relation with its broader social and institutional environment. Understanding these elements of Vietnam’s education system is of vital importance for efforts to improve education systems’ performance in Vietnam and beyond.
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Brownsword, Lisa, David Fisher, Ed Morris, James Smith, and Patrick Kirwan. System-of-Systems Navigator: An Approach for Managing System-of-Systems Interoperability. Fort Belvoir, VA: Defense Technical Information Center, April 2006. http://dx.doi.org/10.21236/ada449276.

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Ellison, Robert J., John Goodenough, Charles Weinstock, and Carol Woody. Survivability Assurance for System of Systems. Fort Belvoir, VA: Defense Technical Information Center, May 2008. http://dx.doi.org/10.21236/ada482224.

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London, Jonathan. Vietnam’s Education System: How Coherent Is It for Learning? Research on Improving Systems of Education (RISE), March 2023. http://dx.doi.org/10.35489/bsg-rise-wp_2023/131.

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The disappointing performance of education systems in developing countries in improving learning outcomes has spurred research aimed at establishing what features of education systems determine their effectiveness or failure in improving learning outcomes. There has been special interest in the challenge of making education systems more coherent for learning, i.e., developing systems in which accountability relations among stakeholders across key elements of education policy design support and sustain strong learning outcomes. In the emergent literature on the political economy of education, a great deal of attention has been directed at Vietnam, a lower-middle income country whose results on assessments of learning have been vastly higher than all other countries in its income group and have even surpassed learning assessment results of many OECD countries. This has led to a raft of research papers asking, “how did Vietnam do it?” Addressing this question, this paper explores Vietnam’s education system’s coherence for learning through an analysis of accountability relations across three key elements of education policy design — delegation, finance, and information. Our aim is to ascertain how features of these policy elements’ practice may variously support or undermine the Communist Party of Vietnam’s objective of promoting quality education and improved learning outcomes for all. The potentially surprising answer to the “how coherent” question posed in the title is, not really that much. Analysis finds that Vietnam’s education system remains weakly "coherent around learning" and is best understood as a “formal process compliant” system that, despite its many strengths, is nonetheless underperforming relative to its potential. The implications of this for efforts to enhance the system’s performance around learning are explored in brief.
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Andronick, June, and Gerwin Klein. Formal System Verification for Trustworthy Embedded Systems. Fort Belvoir, VA: Defense Technical Information Center, April 2011. http://dx.doi.org/10.21236/ada541318.

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Kaffenberger, Michelle, and Marla Spivack. System Coherence for Learning: Applications of the RISE Education Systems Framework. Research on Improving Systems of Education (RISE), January 2022. http://dx.doi.org/10.35489/bsg-risewp_2022/086.

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In recent decades, education systems in most low- and middle-income countries (LMICs) have rapidly expanded access to schooling, but learning has lagged behind. There are many reasons for low learning in LMICs. Proximate determinants (such as insufficient financing or poor school management) receive much attention, but focus on these often ignores underlying system drivers. In this chapter we use a systems approach to describe underlying system dynamics that drive learning outcomes. To do so, we first describe the RISE education systems framework and then apply it to two cases. In the case of Sobral, Brazil, the systems framework illustrates how a coherent package of reforms, improving upon multiple system components, produced positive outcomes. In the case of Indonesia, a reform that increased teacher pay, but did not change underlying system dynamics, had no impact on learning. The chapter shows how a systems approach can help to understand success, diagnose failure, and inform action to bring about improvements to children’s learning.
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Lilavanichakul, Apichaya. Sustainable Agri-Food System and Resilience in Thailand - Exploring Technology-Driven Solutions for a Resilient Future. Asian Productivity Organization, January 2025. https://doi.org/10.61145/gthi4179.

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The agri-food system faces critical challenges from climate change, food insecurity, and rising consumer demands for transparency. This report explores technology-driven solutions such as digital agriculture, vertical farming, and circular economy practices to enhance sustainability and resilience. It emphasizes the role of stakeholders in addressing systemic vulnerabilities exposed by the COVID-19 pandemic and climate disruptions. Adopting equitable practices and stringent climate policies can create a sustainable future for global food systems.
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