Relevant bibliographies by topics / Fog Computing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Fog Computing'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Fog Computing"

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Bhatt, Chintan, and C. K. Bhensdadia. "Fog Computing." International Journal of Grid and High Performance Computing 9, no. 4 (2017): 105–13. http://dx.doi.org/10.4018/ijghpc.2017100107.

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The Internet of Things could be a recent computing paradigm, defined by networks of extremely connected things – sensors, actuators and good objects – communication across networks of homes, buildings, vehicles, and even individuals whereas cloud computing could be ready to keep up with current processing and machine demands. Fog computing provides architectural resolution to deal with some of these issues by providing a layer of intermediate nodes what's referred to as an edge network [26]. These edge nodes provide interoperability, real-time interaction, and if necessary, computational to th
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Chen, Songqing, Tao Zhang, and Weisong Shi. "Fog Computing." IEEE Internet Computing 21, no. 2 (2017): 4–6. http://dx.doi.org/10.1109/mic.2017.39.

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Pagel, Peter, and Stefan Schulte. "Fog Computing." Informatik Spektrum 42, no. 4 (2019): 233–35. http://dx.doi.org/10.1007/s00287-019-01211-z.

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Matt, Christian. "Fog Computing." Business & Information Systems Engineering 60, no. 4 (2018): 351–55. http://dx.doi.org/10.1007/s12599-018-0540-6.

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Mangla, Cherry, Shalli Rani, and Henry Kwame Atiglah. "Secure Data Transmission Using Quantum Cryptography in Fog Computing." Wireless Communications and Mobile Computing 2022 (January 22, 2022): 1–8. http://dx.doi.org/10.1155/2022/3426811.

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Fog computing’s idea is to bring virtual existence into objects used on a daily basis. The “objects” layer of fog architecture is also known as the smart object layer (SOL). SOL has provided the fog network with a strong platform to outperform. Although the fog architecture decentralizes data, uses more data centers, and collects and transmits it to adjacent servers for faster processing in fog networks, it faces several security challenges. The security problems of fog computing need to be alleviated for the exploitation of all benefits of fog computing in classical networks. This article has
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Sookhak, Mehdi, F. Richard Yu, Ying He, et al. "Fog Vehicular Computing: Augmentation of Fog Computing Using Vehicular Cloud Computing." IEEE Vehicular Technology Magazine 12, no. 3 (2017): 55–64. http://dx.doi.org/10.1109/mvt.2017.2667499.

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Yacelga, Andres Leon, Nelson B. Arevalo, and Luis Albarracin Zambrano. "Fog Computing in the Industrial Internet of Things: Challenges, Trends, and Strategies." Fusion: Practice and Applications 13, no. 2 (2023): 91–105. http://dx.doi.org/10.54216/fpa.130208.

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The Industrial Internet of Things (IIoT) has ushered in a new era of connectivity and intelligence in industrial settings. At the heart of this transformative landscape lies Fog Computing, a distributed computing paradigm that brings processing power and intelligence closer to the edge of industrial networks. This paper provides a comprehensive survey of Fog Computing's pivotal role in IIoT, elucidating its significance, challenges, emerging trends, and strategies for successful implementation. We delve into the challenges that industrial environments present for Fog Computing, encompassing is
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Ahuja, Sanjay P., and Niharika Deval. "From Cloud Computing to Fog Computing." International Journal of Fog Computing 1, no. 1 (2018): 1–14. http://dx.doi.org/10.4018/ijfc.2018010101.

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This article describes how in recent years, Cloud Computing has emerged as a fundamental computing paradigm that has significantly changed the approach of enterprises as well as end users towards implementation of Internet technology. The key characteristics such as on-demand resource provision, scalability, rapid elasticity, higher flexibility, and significant cost savings have influenced enterprises of all sizes in the wide and successful adoption of Cloud Computing. Despite numerous advantages, Cloud Computing has its fair share of downsides as well. One of those major concerns is latency i
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R, Dhivya Sree. "Fog Computing in IoT." International Journal of Research Publication and Reviews 4, no. 4 (2023): 3214–15. http://dx.doi.org/10.55248/gengpi.4.423.36600.

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Menon, Varun G., and Joe Prathap. "Vehicular Fog Computing." International Journal of Vehicular Telematics and Infotainment Systems 1, no. 2 (2017): 15–23. http://dx.doi.org/10.4018/ijvtis.2017070102.

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In recent years Vehicular Ad Hoc Networks (VANETs) have received increased attention due to its numerous applications in cooperative collision warning and traffic alert broadcasting. VANETs have been depending on cloud computing for networking, computing and data storage services. Emergence of advanced vehicular applications has led to the increased demand for powerful communication and computation facilities with low latency. With cloud computing unable to satisfy these demands, the focus has shifted to bring computation and communication facilities nearer to the vehicles, leading to the emer
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Dissertations / Theses on the topic "Fog Computing"

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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
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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 distribut
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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
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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 servi
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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 Telemática<br>This 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 th
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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
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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 r
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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 provi
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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 ti
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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 partic
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Books on the topic "Fog Computing"

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Tomar, Ravi, Avita Katal, Susheela Dahiya, Niharika Singh, and Tanupriya Choudhury. Fog Computing. Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003188230.

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Mahmood, Zaigham, ed. Fog Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94890-4.

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Buyya, Rajkumar, and Satish Narayana Srirama, eds. Fog and Edge Computing. John Wiley & Sons, Inc., 2019. http://dx.doi.org/10.1002/9781119525080.

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Tanwar, Sudeep, ed. Fog Computing for Healthcare 4.0 Environments. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-46197-3.

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Kumar, Mohit, Sukhpal Singh Gill, Jitendra Kumar Samriya, and Steve Uhlig, eds. 6G Enabled Fog Computing in IoT. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30101-8.

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Lin, Xiaodong, Jianbing Ni, and Xuemin Shen. Privacy-Enhancing Fog Computing and Its Applications. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02113-9.

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Rahmani, Amir M., Pasi Liljeberg, Jürgo-Sören Preden, and Axel Jantsch, eds. Fog Computing in the Internet of Things. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-57639-8.

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Tiwari, Rajeev, Mamta Mittal, and Lalit Mohan Goyal, eds. Energy Conservation Solutions for Fog-Edge Computing Paradigms. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-3448-2.

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Chang, Wei, and Jie Wu, eds. Fog/Edge Computing For Security, Privacy, and Applications. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-57328-7.

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Thakkar, Hiren Kumar, Chinmaya Kumar Dehury, Prasan Kumar Sahoo, and Bharadwaj Veeravalli, eds. Predictive Analytics in Cloud, Fog, and Edge Computing. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-18034-7.

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Book chapters on the topic "Fog Computing"

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Oppitz, Marcus, and Peter Tomsu. "Fog Computing." In Inventing the Cloud Century. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61161-7_17.

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Rayes, Ammar, and Samer Salam. "Fog Computing." In Internet of Things From Hype to Reality. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99516-8_6.

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Chithaluru, Premkumar, Pallati Narsimhulu, N. Sudhakar Yadav, Priyanka Chawla, and Rajeev Tiwari. "Fog computing." In Cloud and Fog Optimization-based Solutions for Sustainable Developments. CRC Press, 2024. http://dx.doi.org/10.1201/9781003494430-14.

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Kumar, Sudhir. "Fog Computing." In Fundamentals of Internet of Things. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003225584-7.

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Rayes, Ammar, and Samer Salam. "Fog Computing." In Internet of Things from Hype to Reality. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90158-5_6.

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Misra, Sudip, Subhadeep Sarkar, and Subarna Chatterjee. "Fog Computing Applications." In Sensors, Cloud, and Fog: The Enabling Technologies for the Internet of Things. CRC Press, 2019. http://dx.doi.org/10.1201/9780429293986-9.

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Thomas, Priya, and Deepa V. Jose. "Edge/Fog Computing." In Machine Intelligence. Auerbach Publications, 2023. http://dx.doi.org/10.1201/9781003424550-3.

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Lohani, Kaustubh, Prajwal Bhardwaj, and Ravi Tomar. "Fog Computing and Machine Learning." In Fog Computing. Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003188230-10.

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Jaiswal, Kabir, and Niharika Singh. "Fog Computing: Present and Future." In Fog Computing. Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003188230-1.

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Sunyaev, Ali. "Fog and Edge Computing." In Internet Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-34957-8_8.

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Conference papers on the topic "Fog Computing"

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Munro, William J., and Kae Nemoto. "Quantum fog computing." In Quantum Communications and Quantum Imaging XXI, edited by Keith S. Deacon and Ronald E. Meyers. SPIE, 2023. https://doi.org/10.1117/12.2675678.

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Sithole, Sicelo Prince, Naume Sonhera, and Tranos Zuva. "Fog Computing – Desktop Review." In 2024 4th International Multidisciplinary Information Technology and Engineering Conference (IMITEC). IEEE, 2024. https://doi.org/10.1109/imitec60221.2024.10850956.

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Šatkauskas, Nerijus, Algimantas Venčkauskas, and Nerijus Morkevičius. "Fog Computing Service Placement Orchestrator." In 2024 11th International Conference on Electrical and Electronics Engineering (ICEEE). IEEE, 2024. https://doi.org/10.1109/iceee62185.2024.10779266.

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Ahmed, Marwa Farouk, Yasmine N. M. Saleh, and Ayman Adel Abdel–Hamid. "TFCB-Fog: Trust Framework for Cluster-based Fog Computing Environments." In 2024 International Conference on Computer and Applications (ICCA). IEEE, 2024. https://doi.org/10.1109/icca62237.2024.10928157.

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Lal, Roop, Sanjay Singla, and Neelamani Samal. "Navigating the Cloud and Fog: An Extensive Comparative Analysis of Cloud Computing and Fog Computing Architectures." In 2024 2nd International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES). IEEE, 2024. https://doi.org/10.1109/scopes64467.2024.10991096.

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Panchal, Bhupendra, and Preeti Saxena. "Fog Node Selection and Task Scheduling in Fog Computing Environment: A Review." In 2025 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS). IEEE, 2025. https://doi.org/10.1109/sceecs64059.2025.10940161.

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Rabay'a, Ahmad, Eduard Schleicher, and Kalman Graffi. "Fog Computing with P2P: Enhancing Fog Computing Bandwidth for IoT Scenarios." In 2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). IEEE, 2019. http://dx.doi.org/10.1109/ithings/greencom/cpscom/smartdata.2019.00036.

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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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Yannuzzi, M., R. Milito, R. Serral-Gracia, D. Montero, and M. Nemirovsky. "Key ingredients in an IoT recipe: Fog Computing, Cloud computing, and more Fog Computing." In 2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD). IEEE, 2014. http://dx.doi.org/10.1109/camad.2014.7033259.

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Cao, Suzhi, Hao Han, Junyong Wei, Yi Zhao, Shuling Yang, and Lei Yan. "Space Cloud-Fog Computing." In the 3rd International Conference. ACM Press, 2019. http://dx.doi.org/10.1145/3331453.3361637.

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Reports on the topic "Fog Computing"

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Iorga, Michaela, Larry Feldman, Robert Barton, Michael J. Martin, Ned Goren, and Charif Mahmoudi. Fog computing conceptual model. National Institute of Standards and Technology, 2018. http://dx.doi.org/10.6028/nist.sp.500-325.

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Roig, Pedro Juan, Salvador Alcaraz, Katja Gilly, Cristina Bernad, and Carlos Juiz. Formal algebraic description of a fog computing environment. Peeref, 2023. http://dx.doi.org/10.54985/peeref.2304p4360493.

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Percivall, George, ed. The Role of Geospatial in Edge-Fog-Cloud Computing - An OGC White Paper. Open Geospatial Consortium, Inc., 2018. http://dx.doi.org/10.62973/18-004r1.

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Bui, Thai. Using Spammers' Computing Resources for Volunteer Computing. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.1628.

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Pasupuleti, Murali Krishna. Quantum Semiconductors for Scalable and Fault-Tolerant Computing. National Education Services, 2025. https://doi.org/10.62311/nesx/rr825.

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Abstract: Quantum semiconductors are revolutionizing computing by enabling scalable, fault-tolerant quantum processors that overcome the limitations of classical computing. As quantum technologies advance, superconducting qubits, silicon spin qubits, topological qubits, and hybrid quantum-classical architectures are emerging as key solutions for achieving high-fidelity quantum operations and long-term coherence. This research explores the materials, device engineering, and fabrication challenges associated with quantum semiconductors, focusing on quantum error correction, cryogenic control sys
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Killian, Edward. Advanced Computing Architectures for High Performance Computing Engineering Integration. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada522412.

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Ross, Virginia W., and Scott E. Spetka. Grid Computing for High Performance Computing (HPC) Data Centers. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada466685.

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Wachen, John, and Steven McGee. Qubit by Qubit’s Middle School Quantum Camp Evaluation Report for Summer 2021. The Learning Partnership, 2021. http://dx.doi.org/10.51420/report.2021.5.

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Qubit by Qubit’s Middle School Quantum Camp is one of the first opportunities for students as young as eleven to begin learning about the field of quantum computing. In this week-long summer camp, students learn about key concepts of quantum mechanics and quantum computing, including qubits, superposition, and entanglement, basic coding in Python, and quantum gates. By the end of the camp, students can code quantum circuits and run them on a real quantum computer. The Middle School Quantum Camp substantially increased participants’ knowledge about quantum computing, as exhibited by large gains
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Pasupuleti, Murali Krishna. Neuromorphic Nanotech: 2D Materials for Energy-Efficient Edge Computing. National Education Services, 2025. https://doi.org/10.62311/nesx/rr325.

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Abstract The demand for energy-efficient, real-time computing is driving the evolution of neuromorphic computing and edge AI systems. Traditional silicon-based processors struggle with power inefficiencies, memory bottlenecks, and scalability limitations, making them unsuitable for next-generation low-power AI applications. This research report explores how 2D materials, such as graphene, transition metal dichalcogenides (TMDs), black phosphorus, and MXenes, are enabling the development of neuromorphic architectures that mimic biological neural networks for high-speed, ultra-low-power computat
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Shires, Dale, Song Jun Park, Brian Henz, Jerry Clarke, Lam Nguyen, and Kelly Kirk. Asymmetric Core Computing for U.S. Army High-Performance Computing Applications. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada499569.

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