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Simulation of Runtime Performance of Big Data Workflows on the Cloud

Lookup NU author(s): Faris Llwaah, Dr Jacek CalaORCiD, Dr Nigel Thomas



This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).


Big data analysis has become a vital tool in many disciplines. Due to its intensive nature, big data analysis is often performed in cloud computing environments. Cloud computing offers the potential for large scale parallelism and scalable provision. However, determining an optimal deployment can be an expensive operation and therefore some form of prediction of performance prior to deployment would be extremely useful. In this paper we explore the deployment of one complex such problem, the NGS pipeline. We use provenance execution data to populate models simulated in WorkflowSim and CloudSim. This allows us to explore different scenarios for runtime properties.

Publication metadata

Author(s): Llwaah F, Cala J, Thomas N

Editor(s): Fiems, D; Paolieri, M

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 13th European Performance Engineering Workshop (EPEW)

Year of Conference: 2016

Pages: 141-155

Print publication date: 16/09/2016

Online publication date: 16/09/2016

Acceptance date: 15/07/2016

Date deposited: 31/10/2016

ISSN: 0302-9743

Publisher: Springer


DOI: 10.1007/978-3-319-46433-6_10

Library holdings: Search Newcastle University Library for this item

Series Title: Lecture Notes in Computer Science

ISBN: 9783319464336