M. Assunção, M. Netto, B. Peterson, Lakshminarayanan Renganarayana, J. Rofrano, Chris Ward, Christopher Young
{"title":"CloudAffinity: A framework for matching servers to cloudmates","authors":"M. Assunção, M. Netto, B. Peterson, Lakshminarayanan Renganarayana, J. Rofrano, Chris Ward, Christopher Young","doi":"10.1109/NOMS.2012.6211901","DOIUrl":null,"url":null,"abstract":"Increasingly organizations are considering moving their workloads to clouds to take advantage of the anticipated benefits of a more cost effective and agile IT infrastructure. A key component of a cloud service, as it is exposed to the consumer, is the published selection of instance resource configurations (CPU, memory, and disk). The number of instance configurations, as well as the specific values that characterize them, form important decisions for the cloud service provider. This paper explores these resource configurations; examines how well a traditional data center fits into the cloud model from a resource allocation perspective; and proposes a framework, named CloudAffinity, aimed at selecting an optimal number of configurations based on customer requirements.","PeriodicalId":364494,"journal":{"name":"2012 IEEE Network Operations and Management Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Network Operations and Management Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NOMS.2012.6211901","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Increasingly organizations are considering moving their workloads to clouds to take advantage of the anticipated benefits of a more cost effective and agile IT infrastructure. A key component of a cloud service, as it is exposed to the consumer, is the published selection of instance resource configurations (CPU, memory, and disk). The number of instance configurations, as well as the specific values that characterize them, form important decisions for the cloud service provider. This paper explores these resource configurations; examines how well a traditional data center fits into the cloud model from a resource allocation perspective; and proposes a framework, named CloudAffinity, aimed at selecting an optimal number of configurations based on customer requirements.