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Title

On-demand minimum cost benchmarking for intermediate dataset storage in scientific cloud workflow systems

Author(s)

Yuan, Dong;  Yang, Yun;  Liu, Xiao;  Chen, Jinjun

Abstract

Many scientific workflows are data intensive: large volumes of intermediate datasets are generated during their execution. Some valuable intermediate datasets need to be stored for sharing or reuse. Traditionally, they are selectively stored according to the system storage capacity, determined manually. As doing science on clouds has become popular nowadays, more intermediate datasets in scientific cloud workflows can be stored by different storage strategies based on a pay-as-you-go model. In this paper, we build an intermediate data dependency graph (IDG) from the data provenances in scientific workflows. With the IDG, deleted intermediate datasets can be regenerated, and as such we develop a novel algorithm that can find a minimum cost storage strategy for the intermediate datasets in scientific cloud workflow systems. The strategy achieves the best trade-off of computation cost and storage cost by automatically storing the most appropriate intermediate datasets in the cloud storage. This strategy can be utilised on demand as a minimum cost benchmark for all other intermediate dataset storage strategies in the cloud. We utilise Amazon clouds' cost model and apply the algorithm to general random as well as specific astrophysics pulsar searching scientific workflows for evaluation. The results show that benchmarking effectively demonstrates the cost effectiveness over other representative storage strategies.

Publication type

Journal article

Research centre

Swinburne University of Technology. Faculty of Information and Communication Technologies

Source

Journal of Parallel and Distributed Computing, Vol. 71, no. 2, (Feb 2011), pp. 316-332

Publication year

2011

FOR Code(s)

0805 Distributed Computing

Keyword(s)

Cloud computing;  Cost benchmarking;  Dataset storage;  Scientific workflow

Publisher

Academic Press

ISSN

0743-7315

Publisher URL

http://dx.doi.org/10.1016/j.jpdc.2010.09.003

Copyright

Copyright © 2011 Elsevier. The accepted manuscript is reproduced in accordance with the copyright policy of the publisher.

Research Projects

Novel cloud computing based workflow technology for managing large numbers of process instances, Australian Research Council grant number LP0990393

Full text

Peer reviewed