A new energy-aware tasks scheduling approach in fog computing using hybrid meta-heuristic algorithm

In recent years, large computational problems have beensolved by the distributed environment in which applications are executed in parallel. Also, lately, fog computing or edge computing as a new environment is applied to collect data from the devices and preprocessing is done before sending for mai...

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Vydáno v:Journal of parallel and distributed computing Ročník 143; s. 88 - 96
Hlavní autoři: Hosseinioun, Pejman, Kheirabadi, Maryam, Kamel Tabbakh, Seyed Reza, Ghaemi, Reza
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Inc 01.09.2020
Témata:
DVFS
Energy consumption
Fog computing
Meta-heuristic Algorithm
Task scheduling
Fog computing
Task scheduling
Energy consumption
Meta-heuristic Algorithm
DVFS
ISSN:0743-7315, 1096-0848
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Shrnutí:In recent years, large computational problems have beensolved by the distributed environment in which applications are executed in parallel. Also, lately, fog computing or edge computing as a new environment is applied to collect data from the devices and preprocessing is done before sending for main processing in cloud computing. Since one of the crucial issues in such systems is task scheduling, this issue is addressed by considering reducing energy consumption. In this study, an energy-aware method is introduced by using the Dynamic Voltage and Frequency Scaling (DVFS) technique to reduce energy consumption. In addition, in order to construct valid task sequences, a hybrid Invasive Weed Optimization and Culture (IWO-CA) evolutionary algorithm is applied. The experimental results revealed that the proposed algorithm improves some current algorithms in terms of energy consumption. •Proposing an energy-aware task scheduling approach to minimize energy consumption in fog computing.•Presenting a hybrid invasive weed optimization (IWO) along with the cultural evolution algorithm (CEA) for proposed task scheduling approach in fog computing.•Guaranteeing optimal solutions for proposed energy-aware task scheduling approach based on maximum level of QoS factors.
ISSN:0743-7315
1096-0848
DOI:10.1016/j.jpdc.2020.04.008