Task Offloading in Edge and Cloud Computing: A Survey on Mathematical, Artificial Intelligence and Control Theory Solutions

Autor: Nathalie Mitton, Marios Avgeris, Nikolaos Athanasopoulos, John Violos, Aris Leivadeas, Dimitrios Dechouniotis, Symeon Papavassiliou, Nina Santi, Dimitrios Spatharakis, Firdose Saeik
Přispěvatelé: Ecole de Technologie Supérieure [Montréal] (ETS), National Technical University of Athens [Athens] (NTUA), Self-organizing Future Ubiquitous Network (FUN), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Queen's University [Belfast] (QUB)
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Computer Networks and Communications
Computer science
Cloud computing
02 engineering and technology
Task (project management)
Resource Allocation
[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing
[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]
Resource (project management)
Control theory
Artificial Intelligence
0202 electrical engineering
electronic engineering
information engineering
Edge Computing
Control Theory
Edge computing
Task Offloading
business.industry
End user
020206 networking & telecommunications
Telecommunications network
020201 artificial intelligence & image processing
Enhanced Data Rates for GSM Evolution
Artificial intelligence
Mathematical Optimization
[INFO.INFO-DC]Computer Science [cs]/Distributed
Parallel
and Cluster Computing [cs.DC]
business
Zdroj: Computer Networks
Computer Networks, 2021, 195, ⟨10.1016/j.comnet.2021.108177⟩
Saik, F, Avgeris, M, Spatharakis, D, Santi, N, Dechouniotis, D, Violos, J, Leivadeas, A, Athanasopoulos, N, Mitton, N & Papavassiliou, S 2021, ' Task Offloading in Edge and Cloud Computing: A Survey on Mathematical, Artificial Intelligence and Control Theory Solutions ', Computer Networks, vol. 195, 108177 . https://doi.org/10.1016/j.comnet.2021.108177
HAL
Computer Networks, Elsevier, 2021, 195, ⟨10.1016/j.comnet.2021.108177⟩
ISSN: 1389-1286
DOI: 10.1016/j.comnet.2021.108177⟩
Popis: International audience; Next generation communication networks are expected to accommodate a high number of new and resource-voracious applications that can be offered to a large range of end users. Even though end devices are becoming more powerful, the available local resources cannot cope with the requirements of these applications. This has created a new challenge called task offloading, where computation intensive tasks need to be offloaded to more resource powerful remote devices. Naturally, the Cloud Computing is a well-tested infrastructure that can facilitate the task offloading. However, Cloud Computing as a centralized and distant infrastructure creates significant communication delays that cannot satisfy the requirements of the emerging delay-sensitive applications. To this end, the concept of Edge Computing has been proposed, where the Cloud Computing capabilities are repositioned closer to the end devices at the edge of the network. This paper provides a detailed survey of how the Edge and/or Cloud can be combined together to facilitate the task offloading problem. Particular emphasis is given on the mathematical, artificial intelligence and control theory optimization approaches that can be used to satisfy the various objectives, constraints and dynamic conditions of this end-to-end application execution approach. The survey concludes with identifying open challenges and future directions of the problem at hand.
Databáze: OpenAIRE
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