{"title":"Building a performance model of streaming media applications in utility data center environment","authors":"L. Cherkasova, Loren Staley","doi":"10.1109/CCGRID.2003.1199352","DOIUrl":null,"url":null,"abstract":"Utility Data Center (UDC) provides a flexible, cost-effective infrastructure to support the hosting of applications for Internet services. In order to enable the design of a \"utility-aware\" streaming media service which automatically requests the necessary resources from UDC infrastructure, we introduce a set of benchmarks for measuring the basic capacities of streaming media systems. The benchmarks allow one to derive the scaling rules of server capacity for delivering media files which are: i) encoded at different bit rates, ii) streamed from memory vs disk. Using an experimental testbed, we show that these scaling rules are non-trivial. In this paper, we develop a workload-aware, media server performance model which is based on a cost function derived from the set of basic benchmark measurements. We validate this performance model by comparing the predicted and measured media server capacities for a set of synthetic workloads.","PeriodicalId":433323,"journal":{"name":"CCGrid 2003. 3rd IEEE/ACM International Symposium on Cluster Computing and the Grid, 2003. Proceedings.","volume":"307 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CCGrid 2003. 3rd IEEE/ACM International Symposium on Cluster Computing and the Grid, 2003. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGRID.2003.1199352","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26
Abstract
Utility Data Center (UDC) provides a flexible, cost-effective infrastructure to support the hosting of applications for Internet services. In order to enable the design of a "utility-aware" streaming media service which automatically requests the necessary resources from UDC infrastructure, we introduce a set of benchmarks for measuring the basic capacities of streaming media systems. The benchmarks allow one to derive the scaling rules of server capacity for delivering media files which are: i) encoded at different bit rates, ii) streamed from memory vs disk. Using an experimental testbed, we show that these scaling rules are non-trivial. In this paper, we develop a workload-aware, media server performance model which is based on a cost function derived from the set of basic benchmark measurements. We validate this performance model by comparing the predicted and measured media server capacities for a set of synthetic workloads.
公用事业数据中心(Utility Data Center, UDC)提供了一种灵活的、经济高效的基础设施,以支持Internet服务的应用程序托管。为了实现“实用感知”流媒体服务的设计,该服务能够自动从UDC基础设施请求必要的资源,我们引入了一组基准来测量流媒体系统的基本容量。这些基准测试允许我们推导出传输媒体文件的服务器容量的缩放规则:i)以不同的比特率编码,ii)从内存和磁盘传输。通过一个实验平台,我们证明了这些缩放规则是非平凡的。在本文中,我们开发了一个工作负载感知的媒体服务器性能模型,该模型基于从基本基准测量集派生的成本函数。我们通过比较一组合成工作负载的预测和测量的媒体服务器容量来验证此性能模型。