Affiliation:
1. University of Brasilia
Abstract
Fog computing is a paradigm that allows the provisioning of computational resources and services at the edge of the network, closer to the end devices and users, complementing cloud computing. The heterogeneity and large number of devices are challenges to obtaining optimized resource allocation in this environment. Over time, some surveys have been presented on resource management in fog computing. However, they now lack a broader and deeper view about this subject, considering the recent publications. This article presents a systematic literature review with a focus on resource allocation for fog computing, and in a more comprehensive way than the existing works. The survey is based on 108 selected publications from 2012 to 2022. The analysis has exposed their main techniques, metrics used, evaluation tools, virtualization methods, architecture, and domains where the proposed solutions were applied. The results show an updated and comprehensive view about resource allocation in fog computing. The main challenges and open research questions are discussed, and a new fog computing resource management cycle is proposed.
Funder
CAPES, a Brazilian institution
Publisher
Association for Computing Machinery (ACM)
Subject
General Computer Science,Theoretical Computer Science
Reference205 articles.
1. Fog computing for 5G tactile industrial internet of things: QoE-aware resource allocation model;Aazam Mohammad;IEEE Transactions on Industrial Informatics,2019
2. Mohammad Aazam and Eui-Nam Huh. 2015. Dynamic resource provisioning through fog micro datacenter. In 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops). IEEE, 105–110.
3. Fog computing micro datacenter based dynamic resource estimation and pricing model for IoT;Aazam Mohammad;Proceedings - International Conference on Advanced Information Networking and Applications, AINA,2015
4. Mohammad Aazam, Marc St.-Hilaire, Chung-Horng Lung, and Ioannis Lambadaris. 2016. MeFoRE: QoE based resource estimation at Fog to enhance QoS in IoT. In 2016 23rd International Conference on Telecommunications (ICT). IEEE, 1–5.
5. Mohammad Aazam, Marc St.-Hilaire, Chung-Horng Lung, and Ioannis Lambadaris. 2016. PRE-Fog: IoT trace based probabilistic resource estimation at Fog. In 2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC). IEEE, 12–17.
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