{"title":"A grid service broker for scheduling distributed data-oriented applications on global grids","authors":"S. Venugopal, R. Buyya, L. Winton","doi":"10.1145/1028493.1028506","DOIUrl":null,"url":null,"abstract":"Large communities of researchers distributed around the world are engaged in analyzing huge collections of data generated by scientific instruments and replicated on distributed resources. In such an environment, scientists need to have the ability to carry out their studies by transparently accessing distributed data and computational resources. In this paper, we propose and develop a Grid broker that mediates access to distributed resources by (a) discovering suitable data sources for a given analysis scenario, (b) suitable computational resources, (c) optimally mapping analysis jobs to resources, (d) deploying and monitoring job execution on selected resources, (e) accessing data from local or remote data source during job execution and (f) collating and presenting results. The broker supports a declarative and dynamic parametric programming model for creating grid applications. We have used this model in grid-enabling a high energy physics analysis application (Belle Analysis Software Framework) on a grid testbed having resources distributed across Australia.","PeriodicalId":313448,"journal":{"name":"Middleware for Grid Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2004-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"197","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Middleware for Grid Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1028493.1028506","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 197
Abstract
Large communities of researchers distributed around the world are engaged in analyzing huge collections of data generated by scientific instruments and replicated on distributed resources. In such an environment, scientists need to have the ability to carry out their studies by transparently accessing distributed data and computational resources. In this paper, we propose and develop a Grid broker that mediates access to distributed resources by (a) discovering suitable data sources for a given analysis scenario, (b) suitable computational resources, (c) optimally mapping analysis jobs to resources, (d) deploying and monitoring job execution on selected resources, (e) accessing data from local or remote data source during job execution and (f) collating and presenting results. The broker supports a declarative and dynamic parametric programming model for creating grid applications. We have used this model in grid-enabling a high energy physics analysis application (Belle Analysis Software Framework) on a grid testbed having resources distributed across Australia.