Abstract
Scientific workflow application are used to model complex scientific applications in the fields such as Physics, Astronomy and Bio-Informatics. The efficient execution of these applications require access to huge heterogeneous and scalable resources. Recently, there has been a growing interest by scientific community to use cloud platform to deploy scientific workflow applications, because of its support to provide access to unlimited resources. However, main concern in executing these application in cloud platform is task scheduling and resource allocation. In the proposed work, swarm intelligence based W-MOPSO algorithm has been used for scheduling the tasks of scientific workload to the virtual machines of the cloud data center. The proposed system has been evaluated for executing Montage scientific workflow application with different inertia value.
Published Version
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