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Grid data streaming applications are novel from others in that they require real-time data supply while the processing is going on, which necessitates harmonious collaborations among processors, bandwidth and storage. Traditional scheduling approaches may not be sufficient for such applications, for they usually focus on only one aspect of resources, mainly computational resources. A resource management...
Data streaming applications, usually composed with sequential/parallel tasks in a data pipeline form, bring new challenges to task scheduling and resource allocation in grid environments. Due to high volumes of data and relatively limit storage capability, resource allocation and data streaming have to be storage aware. In this paper, genetic algorithm (GA) is adopted for task scheduling of pipelines,...
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