Flexible Provisioning of Service Workflows
Flexible Provisioning of Service Workflows
Service-oriented computing is a promising paradigm for highly distributed and complex computer systems. In such systems, services are offered by provider agents over a computer network and automatically discovered and provisioned by consumer agents that need particular resources or behaviours for their workflows. However, in open systems where there are significant degrees of uncertainty and dynamism and where the agents are self-interested, the provisioning of these services needs to be performed in a more flexible way than has hitherto been considered. To this end, we devise a number of heuristics that vary provisioning according to the predicted performance of provider agents. We then empirically benchmark our algorithms and show that they lead to a 350% improvement in average utility, while successfully completing 5-6 times as many workflows as current approaches.
1-58603-642-4
295-299
Stein, Sebastian
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Payne, Terry R.
0bb13d45-2735-45a3-b72c-472fddbd0bb4
2006
Stein, Sebastian
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Payne, Terry R.
0bb13d45-2735-45a3-b72c-472fddbd0bb4
Stein, Sebastian, Jennings, N. R. and Payne, Terry R.
(2006)
Flexible Provisioning of Service Workflows.
17th European Conference on Artificial Intelligence (ECAI-06), Riva del Garda, Italy.
28 Aug - 01 Sep 2006.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
Service-oriented computing is a promising paradigm for highly distributed and complex computer systems. In such systems, services are offered by provider agents over a computer network and automatically discovered and provisioned by consumer agents that need particular resources or behaviours for their workflows. However, in open systems where there are significant degrees of uncertainty and dynamism and where the agents are self-interested, the provisioning of these services needs to be performed in a more flexible way than has hitherto been considered. To this end, we devise a number of heuristics that vary provisioning according to the predicted performance of provider agents. We then empirically benchmark our algorithms and show that they lead to a 350% improvement in average utility, while successfully completing 5-6 times as many workflows as current approaches.
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ecai06-seb.pdf
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More information
Published date: 2006
Additional Information:
Event Dates: Aug 28th - Sept 1st
Venue - Dates:
17th European Conference on Artificial Intelligence (ECAI-06), Riva del Garda, Italy, 2006-08-28 - 2006-09-01
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 262578
URI: http://eprints.soton.ac.uk/id/eprint/262578
ISBN: 1-58603-642-4
PURE UUID: 8d9d28b2-e1df-4d68-b4ff-c1c779786106
Catalogue record
Date deposited: 15 May 2006
Last modified: 15 Mar 2024 03:30
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Contributors
Author:
Sebastian Stein
Author:
N. R. Jennings
Author:
Terry R. Payne
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