Paper 3

Scientific Work flow 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fic 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.