DocumentCode
2885452
Title
An Adaptive Model of Service Composition Based on Policy Driven and Multi-Agent Negotiation
Author
Tang, Jing-Fan ; Xu, Xiao-liang
Author_Institution
Coll. of Comput. Sci. & Technol., Hangzhou Dianzi Univ.
fYear
2006
fDate
13-16 Aug. 2006
Firstpage
113
Lastpage
118
Abstract
This paper presents an adaptive model of service composition to achieve the optimum profits in the emerging services market, which is based on policy driven and multi-agent negotiation. The negotiation rules will be defined in the policies to determine the conditions for composition and cooperation, such as the accepted range of QoS with corresponding price charge. An agent group will be established to achieve the policy driven negotiation process for service composition, which includes policy agent, evaluation agent and action agent. Policy agent will be responsible for acquiring and parsing negotiation rules from pre-defined policies. Action agent will be responsible for the interactions among the services to reach an agreement. During the negotiation process, evaluation agent will be responsible for doing the evaluation on the bid information received from action agent according to the negotiation rules. And, the action instructions will be generated and sent to action agent for the negotiation on the bids provided by services. Through such policy driven and multi-agent negotiation approach, it can address win-win in the composition and cooperation of the services
Keywords
Internet; multi-agent systems; negotiation support systems; software agents; QoS; action agent; evaluation agent; multiagent negotiation; policy agent; policy driven negotiation; service composition adaptive model; services market; Computer science; Conference management; Cybernetics; Educational institutions; Electronic mail; Logic; Machine learning; Monitoring; Power system management; Web and internet services; Web services; XML; Service composition; multi-agent; policy driven; service negotiation;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location
Dalian, China
Print_ISBN
1-4244-0061-9
Type
conf
DOI
10.1109/ICMLC.2006.258881
Filename
4028042
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