{"title":"Optimizing Resource Consumption and Reducing Power Usage in Data Centers, A Novel Mathematical VM Replacement Model and Efficient Algorithm","authors":"Reza Rabieyan, Ramin Yahyapour, Patrick Jahnke","doi":"10.1007/s10723-024-09772-4","DOIUrl":null,"url":null,"abstract":"<p>This study addresses the issue of power consumption in virtualized cloud data centers by proposing a virtual machine (VM) replacement model and a corresponding algorithm. The model incorporates multi-objective functions, aiming to optimize VM selection based on weights and minimize resource utilization disparities across hosts. Constraints are incorporated to ensure that CPU utilization remains close to the average CPU usage while mitigating overutilization in memory and network bandwidth usage. The proposed algorithm offers a fast and efficient solution with minimal VM replacements. The experimental simulation results demonstrate significant reductions in power consumption compared with a benchmark model. The proposed model and algorithm have been implemented and operated within a real-world cloud infrastructure, emphasizing their practicality.</p>","PeriodicalId":54817,"journal":{"name":"Journal of Grid Computing","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Grid Computing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10723-024-09772-4","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This study addresses the issue of power consumption in virtualized cloud data centers by proposing a virtual machine (VM) replacement model and a corresponding algorithm. The model incorporates multi-objective functions, aiming to optimize VM selection based on weights and minimize resource utilization disparities across hosts. Constraints are incorporated to ensure that CPU utilization remains close to the average CPU usage while mitigating overutilization in memory and network bandwidth usage. The proposed algorithm offers a fast and efficient solution with minimal VM replacements. The experimental simulation results demonstrate significant reductions in power consumption compared with a benchmark model. The proposed model and algorithm have been implemented and operated within a real-world cloud infrastructure, emphasizing their practicality.
本研究通过提出一种虚拟机（VM）替换模型和相应算法，解决了虚拟化云数据中心的能耗问题。该模型包含多目标函数，旨在根据权重优化虚拟机选择，并最大限度地减少主机间的资源利用率差异。该模型纳入了一些约束条件，以确保 CPU 利用率接近平均 CPU 利用率，同时减少内存和网络带宽的过度利用。所提出的算法提供了一种快速高效的解决方案，只需最少的虚拟机替换。实验模拟结果表明，与基准模型相比，功耗显著降低。提出的模型和算法已在现实世界的云基础设施中实施和运行，强调了其实用性。
期刊介绍：
Grid Computing is an emerging technology that enables large-scale resource sharing and coordinated problem solving within distributed, often loosely coordinated groups-what are sometimes termed "virtual organizations. By providing scalable, secure, high-performance mechanisms for discovering and negotiating access to remote resources, Grid technologies promise to make it possible for scientific collaborations to share resources on an unprecedented scale, and for geographically distributed groups to work together in ways that were previously impossible. Similar technologies are being adopted within industry, where they serve as important building blocks for emerging service provider infrastructures.
Even though the advantages of this technology for classes of applications have been acknowledged, research in a variety of disciplines, including not only multiple domains of computer science (networking, middleware, programming, algorithms) but also application disciplines themselves, as well as such areas as sociology and economics, is needed to broaden the applicability and scope of the current body of knowledge.
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