Workflow adaptation as an autonomic computing problem

Lee, K ORCID: https://orcid.org/0000-0002-2730-9150, Sakellariou, R, Paton, NW and Fernandes, AAA, 2007. Workflow adaptation as an autonomic computing problem. In: Proceedings of the 2nd Workshop on Workflows in Support of Large-Scale Science (WORKS07), Monterey Bay, California, 25 June 2007. New York, NY: ACM, pp. 29-34. ISBN 9781595937155

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Abstract

The performance of long running scientific workflows stands to benefit from adapting to changes in their environment. Autonomic Computing provides methodologies for managing run-time adaptations in managed systems. In this paper, we apply the monitoring, analysis, planning and execution (MAPE) model from autonomic computing to support the runtime modification of workflows with the aim of improving their performance. We systematically identify run-time adaptations and indicate how such behaviours can be captured using the MAPE model from the Autonomic Computing community. By characterising these as autonomic computing problems we make a proposal about how workflow adaptation can be achieved.

Item Type:	Chapter in book
Creators:	Lee, K., Sakellariou, R., Paton, N.W. and Fernandes, A.A.A.
Publisher:	ACM
Place of Publication:	New York, NY
Date:	2007
ISBN:	9781595937155
Identifiers:	Number Type 10.1145/1273360.1273366 DOI
Divisions:	Schools > School of Science and Technology
Record created by:	EPrints Services
Date Added:	09 Oct 2015 11:15
Last Modified:	09 Jun 2017 13:54
URI:	https://irep.ntu.ac.uk/id/eprint/25057

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