Presenting a multi-objective method to maintain load balancing to reduce energy consumption using tabu search and frog leaping algorithms in cloud computing VMs

Rezvan Mansoori Seresht

doi:10.53730/ijhs.v6nS1.8188

Presenting a multi-objective method to maintain load balancing to reduce energy consumption using tabu search and frog leaping algorithms in cloud computing VMs

https://doi.org/10.53730/ijhs.v6nS1.8188

Authors

Rezvan Mansoori Seresht Master student of Computer Department, Central Branch, Islamic Azad University, Tehran Branch, Tehran, Iran

Keywords:

Cloud computing, Scheduling, Load balancing, Frog leaping

Abstract

Cloud computing is considered one of the most important applied networks today. Many users around the world benefit from the services of this network. In this network, users first send their requests to cloud servers, and cloud servers then send the responses to these requests after processing them. In this process, the number of requests is much more than the number of servers; Therefore, it is necessary to perform a scheduling operation to ensure that the execution process is performed in the best possible way to reduce time and energy consumption. This research presents a multi-objective method to maintain load balancing to increase efficiency and reduce energy consumption by using tabu search and frog leaping algorithms in cloud computing VMs. This method consists of two parts: in the first part, the tasks are prioritized by the tabu search algorithm, and in the second part, the best machine is selected to be executed by the frog leaping algorithm. The simulation and comparison results indicate the acceptable performance of the proposed method.

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Published

31-05-2022

How to Cite

Seresht, R. M. (2022). Presenting a multi-objective method to maintain load balancing to reduce energy consumption using tabu search and frog leaping algorithms in cloud computing VMs. International Journal of Health Sciences, 6(S1), 12760–12769. https://doi.org/10.53730/ijhs.v6nS1.8188

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Issue

Vol. 6 No. S1 (2022)

Section

Peer Review Articles

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