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
* Auteur correspondant
1 IBC - Institut de Biologie Computationnelle
2 MSR - INRIA - Microsoft Research - Inria Joint Centre
3 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
4 COPPE-UFRJ - COPPE - Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia
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.
Keywords : scientific workflow scientific workflow management system parallel execution multisite cloud Scheduling
Type de document :
Communication dans un congrès
VECPAR, Jun 2016, Porto, Portugal. 12th International Meeting on High Performance Computing for Computational Science, pp.8, 2016, 〈http://vecpar.fe.up.pt/2016/〉
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Contributeur : Patrick Valduriez <>
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Dernière modification le : samedi 27 janvier 2018 - 01:31:47
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Ji Liu, Esther Pacitti, Patrick Valduriez, Marta Mattoso. Scientific Workflow Scheduling with Provenance Support in Multisite Cloud. VECPAR, Jun 2016, Porto, Portugal. 12th International Meeting on High Performance Computing for Computational Science, pp.8, 2016, 〈http://vecpar.fe.up.pt/2016/〉. 〈lirmm-01342190〉

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