{"title":"A GSPN Model to Analyze Performance Parameters in gLite Grids","authors":"Dario Bruneo, M. Scarpa, A. Puliafito","doi":"10.1109/WETICE.2008.39","DOIUrl":null,"url":null,"abstract":"In the last few years grid computing is evolving into a business-innovating technology that is driving commercial adoption. Such a new scenario calls for powerful strategies able to guarantee stringent QoS requirements in order to meet SLAs between customers and provider. For this reason, it is necessary to analyze and predict performance with respect to different load conditions or management strategies. In this paper, we present a methodology to analyze performance in gLite Grids through the use of Generalized Stochastic Petri Nets (GSPNs). We will present a cluster-level model of a typical gLite site taking into account the coexistence between normal and MPI-based jobs.We will investigate the influence of different strategies (e.g., scheduling) on the performance of the whole site highlighting aspects related to both customer and provider point-of-views.","PeriodicalId":259447,"journal":{"name":"2008 IEEE 17th Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises","volume":"323 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE 17th Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WETICE.2008.39","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In the last few years grid computing is evolving into a business-innovating technology that is driving commercial adoption. Such a new scenario calls for powerful strategies able to guarantee stringent QoS requirements in order to meet SLAs between customers and provider. For this reason, it is necessary to analyze and predict performance with respect to different load conditions or management strategies. In this paper, we present a methodology to analyze performance in gLite Grids through the use of Generalized Stochastic Petri Nets (GSPNs). We will present a cluster-level model of a typical gLite site taking into account the coexistence between normal and MPI-based jobs.We will investigate the influence of different strategies (e.g., scheduling) on the performance of the whole site highlighting aspects related to both customer and provider point-of-views.
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