{"title":"Response time-optimized distributed cloud resource allocation","authors":"Matthias Keller, H. Karl","doi":"10.1145/2627566.2627570","DOIUrl":null,"url":null,"abstract":"In the near future many more compute resources will be available at different geographical locations. To minimize the response time of requests, application servers closer to the user can hence be used to shorten network round trip times. However, this advantage is neutralized if the used data centre is highly loaded as the processing time of requests is important as well. We model the request response time as the network round trip time plus the processing time at a data centre.We present a capacitated facility location problem formalization where the processing time is modelled as the sojourn time of a queueing model. We discuss the \\emph{Pareto trade-off} between the number of used data centres and the resulting response time. For example, using fewer data centres could cut expenses but results in high utilization, high response time, and smaller revenues.Previous work presented a non-linear cost function. We prove its \\emph{convexity} and exploit this property in two ways: First, we transform the convex model into a linear model while controlling the maximum approximation error. Second, we used a convex solver instead of a slower non-linear solver.Numerical results on network topologies exemplify our work.","PeriodicalId":91161,"journal":{"name":"Proceedings. Data Compression Conference","volume":"39 1","pages":"47-52"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. Data Compression Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2627566.2627570","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
In the near future many more compute resources will be available at different geographical locations. To minimize the response time of requests, application servers closer to the user can hence be used to shorten network round trip times. However, this advantage is neutralized if the used data centre is highly loaded as the processing time of requests is important as well. We model the request response time as the network round trip time plus the processing time at a data centre.We present a capacitated facility location problem formalization where the processing time is modelled as the sojourn time of a queueing model. We discuss the \emph{Pareto trade-off} between the number of used data centres and the resulting response time. For example, using fewer data centres could cut expenses but results in high utilization, high response time, and smaller revenues.Previous work presented a non-linear cost function. We prove its \emph{convexity} and exploit this property in two ways: First, we transform the convex model into a linear model while controlling the maximum approximation error. Second, we used a convex solver instead of a slower non-linear solver.Numerical results on network topologies exemplify our work.