Virtual Machine Consolidation Algorithm Based on Multi-objective Optimization in Cloud Computing

被引：0

作者：

Hu Z. ^{[1
]}

Xiao H. ^{[1
]}

Li K. ^{[2
]}

机构：

[1] School of Computer Science and Engineering, Central South University, Changsha

[2] College of Computer Science and Electronic Engineering, Hunan University, Changsha

来源：

Hunan Daxue Xuebao/Journal of Hunan University Natural Sciences | 2020年 / 47卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Ant colony system; Cloud computing; Energy saving; Quality of service; Virtual machine consolidation;

D O I：

10.16339/j.cnki.hdxbzkb.2020.02.016

中图分类号：

学科分类号：

摘要：

There exist problems of high energy consumption and high Service Level Agreement (SLA) violation rates in cloud data centers, which urgently need to be resolved. In order to solve the above problems, a Multi-objective Virtual Machine Consolidation Algorithm (MOVMC) was proposed to reduce energy consumption and SLA violation. Taking into account multiple factors including energy consumption, service quality and migration overhead, the virtual machine consolidation problem was constructed as a resource-constrained multi-objective optimization problem. Ant colony system algorithm was employed to perform virtual machine consolidation and obtain the near-optimal mapping relation between virtual machines and hosts as the solution to the multi-objective optimization problem. In order to reduce the algorithm complexity, the double thresholds of CPU utilization were leveraged to judge the host load status and a multi-stage consolidation was performed according to the host load status, in which different consolidation strategies were used. Simulation experiments were conducted on CloudSim platform for MOVMC algorithm and six other virtual machine consolidation algorithms. The experimental results show that, compared with the existing virtual machine consolidation algorithm, the proposed algorithm has significant optimization in terms of energy consumption and SLA violation, and an excellent comprehensive performance. © 2020, Editorial Department of Journal of Hunan University. All right reserved.

引用

页码：116 / 124

页数：8

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