Satoshi Takahashi, H. Nakada, A. Takefusa, T. Kudoh, Maiko Shigeno, Akiko Yoshise
{"title":"Abstract: Virtual Machine Packing Algorithms for Lower Power Consumption","authors":"Satoshi Takahashi, H. Nakada, A. Takefusa, T. Kudoh, Maiko Shigeno, Akiko Yoshise","doi":"10.1109/CloudCom.2012.6427493","DOIUrl":null,"url":null,"abstract":"VM (Virtual Machine)-based flexible capacity man- agement is an effective scheme to reduce total power consumption in the data center. However, there have been the following issues, tradeoff of power-saving and user experience, decision of VM packing in feasible calculation time and collision avoidance of VM migration processes. In order to resolve these issues, we propose a matching-based and a greedy-type VM packing algorithm, which enables to decide a suitable VM packing plan in polynomial time. The experiments evaluate not only a basic performance, but also a feasibility of the algorithms by comparing with optimization solvers. The feasibility experiment uses a super computer trace data prepared by Center for Computational Sciences of Univer- sity of Tsukuba. The basic performance experiment shows that the algorithms reduce total power consumption by between 18% and 50%.","PeriodicalId":6346,"journal":{"name":"2012 SC Companion: High Performance Computing, Networking Storage and Analysis","volume":"34 1","pages":"1517-1518"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 SC Companion: High Performance Computing, Networking Storage and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CloudCom.2012.6427493","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
VM (Virtual Machine)-based flexible capacity man- agement is an effective scheme to reduce total power consumption in the data center. However, there have been the following issues, tradeoff of power-saving and user experience, decision of VM packing in feasible calculation time and collision avoidance of VM migration processes. In order to resolve these issues, we propose a matching-based and a greedy-type VM packing algorithm, which enables to decide a suitable VM packing plan in polynomial time. The experiments evaluate not only a basic performance, but also a feasibility of the algorithms by comparing with optimization solvers. The feasibility experiment uses a super computer trace data prepared by Center for Computational Sciences of Univer- sity of Tsukuba. The basic performance experiment shows that the algorithms reduce total power consumption by between 18% and 50%.