survey

Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions

Authors:

Mohammad Goudarzi,

Marimuthu Palaniswami,

Rajkumar BuyyaAuthors Info & Claims

ACM Computing Surveys, Volume 55, Issue 7

Article No.: 152, Pages 1 - 41

https://doi.org/10.1145/3544836

Published: 15 December 2022 Publication History

Abstract

Fog computing, as a distributed paradigm, offers cloud-like services at the edge of the network with low latency and high-access bandwidth to support a diverse range of IoT application scenarios. To fully utilize the potential of this computing paradigm, scalable, adaptive, and accurate scheduling mechanisms and algorithms are required to efficiently capture the dynamics and requirements of users, IoT applications, environmental properties, and optimization targets. This article presents a taxonomy of recent literature on scheduling IoT applications in Fog computing. Based on our new classification schemes, current works in the literature are analyzed, research gaps of each category are identified, and respective future directions are described.

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Cited By

Umamaheswari P(2024)From Theory to PracticeAdvanced Applications in Osmotic Computing10.4018/979-8-3693-1694-8.ch005(73-89)Online publication date: 29-Mar-2024
https://doi.org/10.4018/979-8-3693-1694-8.ch005
Zhang MShi HMa R(2024)Edge-Distributed IoT Services Assist the Economic Sustainability of LEO Satellite Constellation ConstructionSustainability10.3390/su1604159916:4(1599)Online publication date: 14-Feb-2024
https://doi.org/10.3390/su16041599
Kopras BIdzikowski FBogucka H(2024)A Survey on Reduction of Energy Consumption in Fog Networks—Communications and ComputationsSensors10.3390/s2418606424:18(6064)Online publication date: 19-Sep-2024
https://doi.org/10.3390/s24186064
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Index Terms

Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
2. General and reference
  1. Document types
    1. General literature

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 55, Issue 7

July 2023

813 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3567472

Editor:
Albert Zomaya
University of Sydney, Australia

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Publication History

Published: 15 December 2022

Online AM: 22 June 2022

Accepted: 14 June 2022

Revised: 26 April 2022

Received: 16 January 2022

Published in CSUR Volume 55, Issue 7

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Cited By

Umamaheswari P(2024)From Theory to PracticeAdvanced Applications in Osmotic Computing10.4018/979-8-3693-1694-8.ch005(73-89)Online publication date: 29-Mar-2024
https://doi.org/10.4018/979-8-3693-1694-8.ch005
Zhang MShi HMa R(2024)Edge-Distributed IoT Services Assist the Economic Sustainability of LEO Satellite Constellation ConstructionSustainability10.3390/su1604159916:4(1599)Online publication date: 14-Feb-2024
https://doi.org/10.3390/su16041599
Kopras BIdzikowski FBogucka H(2024)A Survey on Reduction of Energy Consumption in Fog Networks—Communications and ComputationsSensors10.3390/s2418606424:18(6064)Online publication date: 19-Sep-2024
https://doi.org/10.3390/s24186064
He HYang XMi XShen HLiao X(2024)Multi-Agent Deep Reinforcement Learning Based Dynamic Task Offloading in a Device-to-Device Mobile-Edge Computing Network to Minimize Average Task Delay with Deadline ConstraintsSensors10.3390/s2416514124:16(5141)Online publication date: 8-Aug-2024
https://doi.org/10.3390/s24165141
Mi XHe HShen H(2024)A Multi-Agent RL Algorithm for Dynamic Task Offloading in D2D-MEC Network with Energy HarvestingSensors10.3390/s2409277924:9(2779)Online publication date: 26-Apr-2024
https://doi.org/10.3390/s24092779
Rupanetti DKaabouch N(2024)Combining Edge Computing-Assisted Internet of Things Security with Artificial Intelligence: Applications, Challenges, and OpportunitiesApplied Sciences10.3390/app1416710414:16(7104)Online publication date: 13-Aug-2024
https://doi.org/10.3390/app14167104
Zhao XXie GLuo YChen JLiu FBai H(2024)Optimizing storage on fog computing edge servers: A recent algorithm design with minimal interferencePLOS ONE10.1371/journal.pone.030400919:7(e0304009)Online publication date: 10-Jul-2024
https://doi.org/10.1371/journal.pone.0304009
Pioli Lde Macedo DCosta DDantas M(2024)Intelligent Edge-powered Data Reduction: A Systematic Literature ReviewACM Computing Surveys10.1145/365633856:9(1-39)Online publication date: 25-Apr-2024
https://dl.acm.org/doi/10.1145/3656338
Woisetschläger HErben AMayer RWang SJacobsen HSchiavoni VEdinger JCao JJin Z(2024)FLEdge: Benchmarking Federated Learning Applications in Edge Computing SystemsProceedings of the 25th International Middleware Conference10.1145/3652892.3700751(88-102)Online publication date: 2-Dec-2024
https://dl.acm.org/doi/10.1145/3652892.3700751
Nahar AMondal KDas DBuyya R(2024)Clouds on the Road: A Software-Defined Fog Computing Framework for Intelligent Resource Management in Vehicular Ad-Hoc NetworksIEEE Transactions on Mobile Computing10.1109/TMC.2024.341901623:12(12778-12792)Online publication date: Dec-2024
https://doi.org/10.1109/TMC.2024.3419016
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