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AI Augmented Edge and Fog Computing: Trends and Challenges [article]

Shreshth Tuli and Fatemeh Mirhakimi and Samodha Pallewatta and Syed Zawad and Giuliano Casale and Bahman Javadi and Feng Yan and Rajkumar Buyya and Nicholas R. Jennings
2022 arXiv   pre-print
Edge, Fog, Cloud, and Serverless.  ...  We demystify new techniques and draw key insights in Edge, Fog and Cloud resource management-related uses of AI methods and also look at how AI can innovate traditional applications for enhanced Quality  ...  Scholarship at Imperial College London and Australian Research Council Discovery Project. We thank Shikhar Tuli, Zifeng Niu, Runan Wang, Matthew Sheldon and William Plumb for helpful discussions.  ... 
arXiv:2208.00761v1 fatcat:tfrhvlenyvbg7kidoydjzqejai

DeF-DReL: Systematic Deployment of Serverless Functions in Fog and Cloud environments using Deep Reinforcement Learning [article]

Chinmaya Kumar Dehury, Shivananda Poojara, Satish Narayana Srirama
2022 arXiv   pre-print
As a result, we proposed DeF-DReL, a Systematic Deployment of Serverless Functions in Fog and Cloud environments using Deep Reinforcement Learning, using several real-life parameters, such as distance  ...  Fog computing is introduced by shifting cloud resources towards the users' proximity to mitigate the limitations possessed by cloud computing.  ...  A similar approach is used in our previous work [29] that focuses on an efficient service dispersal mechanism for both fog and cloud environment using DRL.  ... 
arXiv:2110.15702v3 fatcat:mfy4jdmbbzdkbkede34hxigg5y

Transformative effects of IoT, Blockchain and Artificial Intelligence on cloud computing: Evolution, vision, trends and open challenges [article]

Sukhpal Singh Gill, Shreshth Tuli, Minxian Xu, Inderpreet Singh, Karan Vijay Singh, Dominic Lindsay, Shikhar Tuli, Daria Smirnova, Manmeet Singh, Udit Jain, Haris Pervaiz, Bhanu Sehgal, Sukhwinder Singh Kaila (+4 others)
2019 arXiv   pre-print
Finally, we proposed a conceptual model for cloud futurology to explore the influence of emerging paradigms and technologies on evolution of cloud computing.  ...  Such system must cope with varying load and evolving usage reflecting societies interaction and dependency on automated computing systems whilst satisfying Quality of Service (QoS) guarantees.  ...  Acknowledgments We would like to thank the editor, area editor and anonymous reviewers for their valuable comments and suggestions to help and improve our research paper.  ... 
arXiv:1911.01941v1 fatcat:seyqgzhqk5cwfdaav2dcjpv254

Implementation analysis of IoT-based offloading frameworks on cloud/edge computing for sensor generated big data

Karan Bajaj, Bhisham Sharma, Raman Singh
2021 Complex & Intelligent Systems  
Various applications and services that are crucial require meeting multiple performance parameters like time-sensitivity and energy efficiency, computation offloading framework comes into play to meet  ...  Computation or data offloading tasks to nearby devices or the fog or cloud structure can aid in achieving the resource requirements of IoT applications.  ...  Acknowledgements This work has been carried out in wireless sensor network research facility in Computer Science and Engineering department of Chitkara University, India.  ... 
doi:10.1007/s40747-021-00434-6 fatcat:q7itavmy6vhjrouldk4qbuuecu

An Intelligent Proposed Model for Task Offloading in Fog-Cloud Collaboration Using Logistics Regression

Muhammad Mazhar Bukhari, Taher M. Ghazal, Sagheer Abbas, M. A. Khan, Umer Farooq, Hasan Wahbah, Munir Ahmad, Khan Muhammad Adnan, Carlos M. Travieso-González
2022 Computational Intelligence and Neuroscience  
Additionally, fog is not the replacement of the cloud, rather supplement to the cloud, both behave like counterparts and offer their services correspondingly to compliance the task needs but fog computing  ...  The problem arises when a decision needs to take what is to be offloaded: data, computation, or application, and more specifically where to offload: either fog or cloud and how much to offload.  ...  Computational Intelligence and Neuroscience  ... 
doi:10.1155/2022/3606068 pmid:35126487 pmcid:PMC8808244 fatcat:h5kkeyu2uvc75lsh3zmdokmnqa

Task Offloading with Multi-Tier Computing Resources in Next Generation Wireless Networks [article]

Kunlun Wang, Jiong Jin, Yang Yang, Tao Zhang, Arumugam Nallanathan, Chintha Tellambura, Bijan Jabbari
2022 arXiv   pre-print
More specifically, multi-tier computing systems compensate for cloud computing through task offloading and dispersing computing tasks to multi-tier nodes along the continuum from the cloud to things.  ...  In order to provide low-latency services to heterogeneous users in the emerging iIoT, multi-tier computing was proposed by effectively combining edge computing and fog computing.  ...  In [65] , Yang et al. also used deep reinforcement learning method in IRS-aided edge computing systems to enhance system security and maximize the sum rate of the down-link task offloading.  ... 
arXiv:2205.13866v1 fatcat:kt7zx34yljfejnxoqo3zjng23i

A Survey on Offloading in Federated Cloud-Edge-Fog Systems with Traditional Optimization and Machine Learning [article]

Binayak Kar, Widhi Yahya, Ying-Dar Lin, Asad Ali
2022 arXiv   pre-print
Edge and fog computing provide similar services with lower latency but with limited capacity, capability, and coverage.  ...  The huge amount of data generated by the Internet of things (IoT) devices needs the computational power and storage capacity provided by cloud, edge, and fog computing paradigms.  ...  An energy-efficient computation offloading mechanism for MEC in 5G heterogeneous networks was proposed in [84] .  ... 
arXiv:2202.10628v1 fatcat:72oyy5unmbcwdn4rrnjy3t7dgu

Optimized Cognitive Learning Model for Energy Efficient Fog-BAN-IoT Networks

S. Kalpana, C. Annadurai
2022 Computer systems science and engineering  
Energy and latency aware features of BAN have been extracted and used to train the proposed fog based learning algorithm to achieve low energy consumption and low-latency scheduling algorithm.  ...  service) parameters such as latency, energy and throughput.  ...  Furthermore, this method is used to select the cluster head for achieving an energy efficient and less latency mechanism.  ... 
doi:10.32604/csse.2022.024685 fatcat:svpdnfcgvbhn7hlazopq3nzcli

2021 Index IEEE Internet of Things Journal Vol. 8

2021 IEEE Internet of Things Journal  
Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., +, JIoT May 1, 2021 7288-7302 Energy-Efficient Deep Reinforced Traffic Grooming in Elastic Optical Networks for Cloud-Fog Computing.  ... 
doi:10.1109/jiot.2022.3141840 fatcat:42a2qzt4jnbwxihxp6rzosha3y

A Comprehensive Study of Caching Effects on Fog Computing Performance

Marwa Mahfodh Abdulqadir, Azar Abid Salih, Omar M. Ahmed, Dathar Abas Hasan, Lailan M. Haji, Sarkar Hasan Ahmed, Rowaida Khalil Ibrahim, Karzan H. Sharif, Hivi Ismat Dino
2021 Asian Journal of Research in Computer Science  
Therefore, Fog computing can be the best solution for the Internet of things to present a practical and secure service for various clients.  ...  Fog computing enables sufficient management for the services and resources by keeping the devices closer to the network edge.  ...  The "Special Issue on Emerging Trends and Challenges in Fog Computing for the Internet of Things" seeks to learn three things: 1) new administration mechanisms for fog computing-enabled deviceto-device  ... 
doi:10.9734/ajrcos/2021/v10i430246 fatcat:fcf2vyeoabcv7kgoqas4cgtpfq

Fog Computing Systems: State of the Art, Research Issues and Future Trends, with a Focus on Resilience [article]

Jose Moura, David Hutchison
2020 arXiv   pre-print
Many future innovative computing services will use Fog Computing Systems (FCS), integrated with Internet of Things (IoT) resources.  ...  using Game Theory, and flexibly programmed with the latest software and virtualization platforms.  ...  We thank the reviewers very much for their constructive and positive comments, which have helped improve the quality of this paper.  ... 
arXiv:1908.05077v4 fatcat:tgtn7rlkpnejxixctw5gorlxnu

Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges [article]

Latif U. Khan, Walid Saad, Zhu Han, Ekram Hossain, Choong Seon Hong
2021 arXiv   pre-print
Third, we propose two IoT use cases of dispersed federated learning that can offer better privacy preservation than federated learning.  ...  The Internet of Things (IoT) will be ripe for the deployment of novel machine learning algorithms for both network and application management.  ...  They considered two use cases such as edge caching and computation offloading. To efficiently enable these use cases, a double deep Q-learning agent was trained using federated learning.  ... 
arXiv:2009.13012v2 fatcat:4oqifqi5czfyxiqe7gjewmuzsq

2021 Index IEEE Transactions on Green Communications and Networking Vol. 5

2021 IEEE Transactions on Green Communications and Networking  
Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  Sensing Using Deep Stacked Fog RAN.  ... 
doi:10.1109/tgcn.2021.3131006 fatcat:6l377alf65ho7ab752c2v2dvve

Fog Computing Algorithms: A Survey and Research Opportunities

Shaifali P. Malukani, C. K. Bhensdadia
2021 Applied Computer Systems  
Fog computing offers better services to end users by bringing processing, storage, and networking closer to them.  ...  The classic Internet of Things-Cloud Computing model faces challenges like high response latency, high bandwidth consumption, and high storage requirement with increasing velocity and volume of generated  ...  [22] consider power consumption and execution time of the modules. Their method uses the Monitor-Analyse-Plan-Execute loop and deep reinforcement learning is used to decide the best destination.  ... 
doi:10.2478/acss-2021-0017 fatcat:wf3pedj7fbddbdfjabz2nugwli

A Review of 4IR/5IR Enabling Technologies and Their Linkage to Manufacturing Supply Chain

Mokesioluwa Fanoro, Mladen Božanić, Saurabh Sinha
2021 Technologies  
Likewise, a review of the fifth industrial revolution is given, and the justification for this development is presented.  ...  A systematic literature review is undertaken to evaluate each enabling technology and the manufacturing supply chain and to provide some theoretical synthesis.  ...  Machine and Deep Learning Machine learning is an artificial technique that uses computers and software to make accurate data predictions.  ... 
doi:10.3390/technologies9040077 fatcat:cq6odciabrbvnccqbv4vnl7jze
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