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Scientific Workflow Scheduling with Provenance Support in Multisite Cloud

Ji Liu 1, 2, 3 Esther Pacitti 3, 1 Patrick Valduriez 3, 1, * Marta Mattoso 4
* Corresponding author
3 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : 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, we propose a multisite task scheduling algorithm that considers the time to generate provenance data. We performed an experimental evaluation of our algorithm using Microsoft Azure multisite cloud and two real-life scientific workflows, i.e. Buzz and Montage. The results show that our scheduling algorithm is up to 49.6% better than baseline algorithms in terms of execution time.
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Submitted on : Tuesday, July 5, 2016 - 2:59:35 PM
Last modification on : Thursday, November 25, 2021 - 11:28:10 AM
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Ji Liu, Esther Pacitti, Patrick Valduriez, Marta Mattoso. Scientific Workflow Scheduling with Provenance Support in Multisite Cloud. VECPAR: Vector and Parallel Processing, Faculty of Engineering of the University of Porto, Portugal, Jun 2016, Porto, Portugal. pp.206-219, ⟨10.1007/978-3-319-61982-8_19⟩. ⟨lirmm-01342190⟩



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