ACDS: Adapting Computational Data Streams for High Performance
Symposium on Parallel and Distributed Processing（2000）
摘要
Data-intensive, interactive applications are an important class of metacomputing (Grid) applications. They are characterized by large, time-varying data flows between data providers and consumers. The topic of this paper is the runtime adaptation of data streams, in response to changes in resource availability and/or in end user requirements, with the goal of continually providing to consumers data at the levels of quality they require. Our approach is one that associates computational objects with data streams. Runtime adaptation is achieved by adjusting objects' actions on streams, by splitting and merging objects, and by migrating them (and the streams on which they operate) across machines and network links. Adaptive streams also react to changes in resource availability detected by online monitoring.
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关键词
end user requirement,associates computational object,adaptive stream,data provider,high performance,adapting computational data streams,resource availability,time-varying data flow,consumers data,runtime adaptation,important class,data stream,user requirements,adaptation,concurrent computing,link adaptation,data streams,distributed processing,availability,collaboration,merging,atmospheric modeling,high performance computing
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