Scientific Workflow Scheduling with Provenance Data in a Multisite Cloud
Résumé
Recently, some Scientific Workflow Management Systems (SWfMSs) with provenance support (e.g. Chiron) have been deployed in the cloud. However, they typically use a single cloud site. In this paper, we consider a multisite cloud, where the data and computing resources are distributed at different sites (possibly in different regions). Based on a multisite architecture of SWfMS, i.e. multisite Chiron, and its provenance model, we propose a multisite task scheduling algorithm that considers the time to generate provenance data. We performed an extensive experimental evaluation of our algorithm using Microsoft Azure multisite cloud and two real-life scientific workflows (Buzz and Montage). The results show that our scheduling algorithm is up to 49.6% better than baseline algorithms in terms of total execution time.
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