{"title":"云计算系统中一种节能的虚拟机调度算法","authors":"Kehe Wu, R. Du, Long Chen, Su Yan","doi":"10.1109/ISCC-C.2013.38","DOIUrl":null,"url":null,"abstract":"Even virtual machines has been widely used as the unit to allocate the processor time or storage spaces by the providers of Cloud Computing systems, the energy consumption pattern of virtual machines in Cloud Computing system is not clear enough yet now. In this paper, we built an energy consumption model of the Cloud Computing system, by using statistical method we can estimate the energy consumption of a virtual machine in a small range of errors in 3%-6%. Then, based on the model, we proposed a virtual machine scheduling algorithm to improve the energy efficiency of the system. First, we set a threshold value of energy consumption for each server in the system, and by analyzing these work plans submitted by each virtual machine, we tested whether the threshold will been exceeded or not. Then, by migrate one/several chosen virtual machines to other physical servers in the system we can reduce the energy consumption of the whole system. Our evaluation shows that the proposed scheduling algorithm can effectively implement energy-saving goals without significant decline of the Quality of Services.","PeriodicalId":313511,"journal":{"name":"2013 International Conference on Information Science and Cloud Computing Companion","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"An Energy-Saving Virtual-Machine Scheduling Algorithm of Cloud Computing System\",\"authors\":\"Kehe Wu, R. Du, Long Chen, Su Yan\",\"doi\":\"10.1109/ISCC-C.2013.38\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Even virtual machines has been widely used as the unit to allocate the processor time or storage spaces by the providers of Cloud Computing systems, the energy consumption pattern of virtual machines in Cloud Computing system is not clear enough yet now. In this paper, we built an energy consumption model of the Cloud Computing system, by using statistical method we can estimate the energy consumption of a virtual machine in a small range of errors in 3%-6%. Then, based on the model, we proposed a virtual machine scheduling algorithm to improve the energy efficiency of the system. First, we set a threshold value of energy consumption for each server in the system, and by analyzing these work plans submitted by each virtual machine, we tested whether the threshold will been exceeded or not. Then, by migrate one/several chosen virtual machines to other physical servers in the system we can reduce the energy consumption of the whole system. Our evaluation shows that the proposed scheduling algorithm can effectively implement energy-saving goals without significant decline of the Quality of Services.\",\"PeriodicalId\":313511,\"journal\":{\"name\":\"2013 International Conference on Information Science and Cloud Computing Companion\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Information Science and Cloud Computing Companion\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCC-C.2013.38\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Information Science and Cloud Computing Companion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCC-C.2013.38","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Energy-Saving Virtual-Machine Scheduling Algorithm of Cloud Computing System
Even virtual machines has been widely used as the unit to allocate the processor time or storage spaces by the providers of Cloud Computing systems, the energy consumption pattern of virtual machines in Cloud Computing system is not clear enough yet now. In this paper, we built an energy consumption model of the Cloud Computing system, by using statistical method we can estimate the energy consumption of a virtual machine in a small range of errors in 3%-6%. Then, based on the model, we proposed a virtual machine scheduling algorithm to improve the energy efficiency of the system. First, we set a threshold value of energy consumption for each server in the system, and by analyzing these work plans submitted by each virtual machine, we tested whether the threshold will been exceeded or not. Then, by migrate one/several chosen virtual machines to other physical servers in the system we can reduce the energy consumption of the whole system. Our evaluation shows that the proposed scheduling algorithm can effectively implement energy-saving goals without significant decline of the Quality of Services.