{"title":"A NSGA-II-based approach for service resource allocation in Cloud","authors":"Boxiong Tan, Hui Ma, Yi Mei","doi":"10.1109/CEC.2017.7969618","DOIUrl":null,"url":null,"abstract":"Web service and Cloud computing have significantly reformed the software industry. The need for web service allocation in the cloud environment is increasing dramatically. In order to reduce the cost for service providers as well as improve the utilization of cloud resource for cloud providers, this paper formulates the web service resource allocation in cloud environment problem as a two-level multi-objective bin packing problem. It proposes a NSGA-II-based algorithm with specifically designed genetic operators. We are compared with two varieties of the algorithm. The results show that the proposed algorithm can provide reasonably good results with low violation rate.","PeriodicalId":335123,"journal":{"name":"2017 IEEE Congress on Evolutionary Computation (CEC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Congress on Evolutionary Computation (CEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEC.2017.7969618","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
Abstract
Web service and Cloud computing have significantly reformed the software industry. The need for web service allocation in the cloud environment is increasing dramatically. In order to reduce the cost for service providers as well as improve the utilization of cloud resource for cloud providers, this paper formulates the web service resource allocation in cloud environment problem as a two-level multi-objective bin packing problem. It proposes a NSGA-II-based algorithm with specifically designed genetic operators. We are compared with two varieties of the algorithm. The results show that the proposed algorithm can provide reasonably good results with low violation rate.