Scienti c Work ow Scheduling with Provenance Data in a Multisite Cloud


Authors: Ji Liu, Esther Pacitti, Patrick Valduriez, and Marta Mattoso

Volume 33 (2017)

Abstract


Recently, some Scienti c 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 differerent 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 scientifi c 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.