{"title":"Design and evaluation of a resource selection framework for Grid applications","authors":"Chuang Liu, Lingyun Yang, Ian T Foster, D. Angulo","doi":"10.1109/HPDC.2002.1029904","DOIUrl":null,"url":null,"abstract":"While distributed, heterogeneous collections of computers (\"Grids\") can in principle be used as a computing platform, in practice the problems of first discovering and then organizing resources to meet application requirements are difficult. We present a general-purpose resource selection framework that addresses these problems by defining a resource selection service for locating Grid resources that match application requirements. At the heart of this framework is a simple, but powerful, declarative language based on a technique called set matching, which extends the Condor matchmaking framework to support both single-resource and multiple-resource selection. This framework also provides an open interface for loading application-specific mapping modules to personalize the resource selector. We present results obtained when this framework is applied in the context of a computational astrophysics application, Cactus. These results demonstrate the effectiveness of our technique.","PeriodicalId":279053,"journal":{"name":"Proceedings 11th IEEE International Symposium on High Performance Distributed Computing","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"250","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 11th IEEE International Symposium on High Performance Distributed Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPDC.2002.1029904","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 250
Abstract
While distributed, heterogeneous collections of computers ("Grids") can in principle be used as a computing platform, in practice the problems of first discovering and then organizing resources to meet application requirements are difficult. We present a general-purpose resource selection framework that addresses these problems by defining a resource selection service for locating Grid resources that match application requirements. At the heart of this framework is a simple, but powerful, declarative language based on a technique called set matching, which extends the Condor matchmaking framework to support both single-resource and multiple-resource selection. This framework also provides an open interface for loading application-specific mapping modules to personalize the resource selector. We present results obtained when this framework is applied in the context of a computational astrophysics application, Cactus. These results demonstrate the effectiveness of our technique.