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Performance analysis of scheduling algorithms for dynamic workflow applications

Citation

Zhou, C and Garg, SK, Performance analysis of scheduling algorithms for dynamic workflow applications, Proceedings of the 2015 IEEE International Congress on Big Data, 27 June - 2 July 2015, New York New York, pp. 222-229. ISBN 978-1-4673-7277-0 (2015) [Refereed Conference Paper]

Copyright Statement

Copyright 2015 IEEE

DOI: doi:10.1109/BigDataCongress.2015.39

Abstract

In recent years, Big Data has changed how we do computing. Even though we have large scale infrastructure such as Cloud computing and several platforms such as Hadoop available to process the workloads, with Big Data there is a high level of uncertainty that has been introduced in how an application processes the data. Data in general comes in different formats, at different speed and at different volume. Processing consists of not just one application but several applications combined to form a workflow to achieve a certain goal. With data variation and at different speed, applications, execution and resource needs will also vary at runtime. These are called dynamic workflows. One can say that we can just throw more and more resources during runtime. However this is not an effective way as it can lead to, in the best case, resource wastage or monetary loss and in the worst case, delivery of outcomes much later than when it is required. Thus, scheduling algorithms play an important role in efficient execution of dynamic workflow applications. In this paper, we evaluate several most commonly used workflow scheduling algorithms to understand which algorithm will be the best for the efficient execution of dynamic workflows.

Item Details

Item Type:Refereed Conference Paper
Keywords:cloud computing, dynamic workflow
Research Division:Information and Computing Sciences
Research Group:Distributed Computing
Research Field:Distributed and Grid Systems
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Application Tools and System Utilities
Author:Zhou, C (Mr Chaochao Zhou)
Author:Garg, SK (Dr Saurabh Garg)
ID Code:102587
Year Published:2015
Web of Science® Times Cited:3
Deposited By:Information and Communication Technology
Deposited On:2015-08-28
Last Modified:2018-01-16
Downloads:0

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