Cat-Squirrel Optimization Algorithm for VM Migration in a Cloud Computing Platform

IF 4.1 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal on Semantic Web and Information Systems Pub Date : 2022-01-01 DOI:10.4018/ijswis.297142
C. A. Kumar, P. Sivakumar
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引用次数: 9

Abstract

This paper introduces an approach for the VM migration based on optimization algorithm, named CS in cloud. The provider to be selected is carried out with the usage of multiple constraints, like delay, bandwidth, cost, and load. Subsequently, the effective searching criteria are computed for finding the optimal service on the basis of fitness constraints. The searching criteria are formulated as optimization problems, which are tackled using CS. The proposed CS is designed by integrating CSO with the SSA such that the fitness function is evaluated for the optimal VM migration by considering several parameters, such as delay, cost, bandwidth, and load. Thus, the cloud manager will perform the migration of VM in cloud based on proposed CS-based VM migration approach. The performance of the CS-based VM migration is evaluated in terms of delay, cost, and load. The proposed CS-based VM migration method achieves the minimal delay of 0.146, minimal cost of 0.052, and the minimal load of 0.182.
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云计算平台下虚拟机迁移的猫松鼠优化算法
本文介绍了一种基于优化算法的虚拟机迁移方法,即云中的CS。要选择的提供者是在使用多个约束条件(如延迟、带宽、成本和负载)的情况下执行的。然后,在适应度约束的基础上,计算出寻找最优服务的有效搜索准则。将搜索标准表述为优化问题,并利用CS对其进行求解。该算法将CSO与SSA相结合,通过考虑延迟、成本、带宽和负载等参数,对适应度函数进行最优VM迁移评估。因此,云管理人员将根据提出的基于cs的VM迁移方法执行云中的VM迁移。从时延、成本和负载三个方面评估基于cs的虚拟机迁移的性能。提出的基于cs的虚拟机迁移方法实现了最小延迟0.146,最小开销0.052,最小负载0.182。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.20
自引率
12.50%
发文量
51
审稿时长
20 months
期刊介绍: The International Journal on Semantic Web and Information Systems (IJSWIS) promotes a knowledge transfer channel where academics, practitioners, and researchers can discuss, analyze, criticize, synthesize, communicate, elaborate, and simplify the more-than-promising technology of the semantic Web in the context of information systems. The journal aims to establish value-adding knowledge transfer and personal development channels in three distinctive areas: academia, industry, and government.
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