Hao Wei, Shurui Zhou, Ting Yang, Rui Zhang, Qianxiang Wang
{"title":"Elastic resource management for heterogeneous applications on PaaS","authors":"Hao Wei, Shurui Zhou, Ting Yang, Rui Zhang, Qianxiang Wang","doi":"10.1145/2532443.2532451","DOIUrl":null,"url":null,"abstract":"Elastic resource management is one of the key characteristics of cloud computing systems. Existing elastic approaches focus mainly on single resource consumption such as CPU consumption, rarely considering comprehensively various features of applications. Applications deployed on a PaaS are usually heterogeneous. While sharing the same resource, these applications are usually quite different in resource consuming. How to deploy these heterogeneous applications on the smallest size of hardware thus becomes a new research topic. In this paper, we take into consideration application's CPU consumption, I/O consumption, consumption of other server resources and application's request rate, all of which are defined as application features. This paper proposes a practical and effective elasticity approach based on the analysis of application features. The evaluation experiment shows that, compared with traditional approach, our approach can save up to 32.8% VMs without significant increase of average response time and SLA violation.","PeriodicalId":362187,"journal":{"name":"Proceedings of the 5th Asia-Pacific Symposium on Internetware","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 5th Asia-Pacific Symposium on Internetware","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2532443.2532451","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Elastic resource management is one of the key characteristics of cloud computing systems. Existing elastic approaches focus mainly on single resource consumption such as CPU consumption, rarely considering comprehensively various features of applications. Applications deployed on a PaaS are usually heterogeneous. While sharing the same resource, these applications are usually quite different in resource consuming. How to deploy these heterogeneous applications on the smallest size of hardware thus becomes a new research topic. In this paper, we take into consideration application's CPU consumption, I/O consumption, consumption of other server resources and application's request rate, all of which are defined as application features. This paper proposes a practical and effective elasticity approach based on the analysis of application features. The evaluation experiment shows that, compared with traditional approach, our approach can save up to 32.8% VMs without significant increase of average response time and SLA violation.