文章基本信息

标题：Spider Monkey Optimization Algorithm for Load Balancing in Cloud Computing Environments
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作者：Sawsan Alshattnawi ; Mohammad AL-Marie
期刊名称：The International Arab Journal of Information Technology
印刷版ISSN：1683-3198
出版年度：2021
卷号：18
期号：5
DOI：10.34028/iajit/18/5/13
语种：English
出版社：Zarqa Private University
摘要：Scheduling of tasks is one of the main concerns in the Cloud Computing environment. The whole system performance depends on the used scheduling algorithm. The scheduling objective is to distribute tasks between the Virtual Machines and balance the load to prevent any virtual machine from being overloaded while other is underloaded. The problem of scheduling is considered an NP-hard optimization problem. Therefore, many heuristics have been proposed to solve this problem up to now. In this paper, we propose a new Spider Monkeys algorithm for load balancing called Spider Monkey Optimization Inspired Load Balancing (SMO-LB) based on mimicking the foraging behavior of Spider Monkeys. It aims to balance the load among virtual machines to increase the performance by reducing makespan and response time. Experimental results show that our proposed method reduces tasks' average response time to 10.7 seconds compared to 24.6 and 30.8 seconds for Round Robin and Throttled methods respectively. Also, the makespan was reduced to 21.5 seconds compared to 35.5 and 53.0 seconds for Round Robin and Throttled methods respectively.
关键词：Cloud computing;load balancing;metaheuristic optimization;spider monkeys optimization;tasks scheduling