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An optimal scheduling method in iot-fog-cloud network using combination of aquila optimizer and african vultures optimization
Authors
Khalid Alnowibet
Azadeh Hoshyar
+3 more
Houman Kosarirad
Qing Liu
Sajad Meisami
Publication date
1 January 2023
Publisher
MDPI
Doi
Cite
Abstract
Today, fog and cloud computing environments can be used to further develop the Internet of Things (IoT). In such environments, task scheduling is very efficient for executing user requests, and the optimal scheduling of IoT task requests increases the productivity of the IoT-fog-cloud system. In this paper, a hybrid meta-heuristic (MH) algorithm is developed to schedule the IoT requests in IoT-fog-cloud networks using the Aquila Optimizer (AO) and African Vultures Optimization Algorithm (AVOA) called AO_AVOA. In AO_AVOA, the exploration phase of AVOA is improved by using AO operators to obtain the best solution during the process of finding the optimal scheduling solution. A comparison between AO_AVOA and methods of AVOA, AO, Firefly Algorithm (FA), particle swarm optimization (PSO), and Harris Hawks Optimization (HHO) according to performance metrics such as makespan and throughput shows the high ability of AO_AVOA to solve the scheduling problem in IoT-fog-cloud networks. © 2023 by the authors
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Last time updated on 16/09/2023