A Reputation-Based Multi-Agent Model for Network Resource Selection
- 1
- 2
- 3
Abstract
Because of the anonymity and openness of online transactions and the richness of network resources, the problems of the credibility of the online trading and the exact selection of network resources have become acute. For this reason, a reputation-based multi-agent model for network resource selection (RMNRS) is presented. The model divides the network into numbers of trust domains. Each domain has one domain-agent and several entity-agents. The model prevents the inconsistency of information that is maintained by differ-ent agents through the periodically communication between the agents. The model enables the consumers to receive responses from agents significantly quicker than that of traditional models, because the global reputation values of service providers and consumers are evaluated and updated dynamically after each transaction. And the model allocates two global reputation values to each entity and takes the recognition value that how much the service provider knows the service into account. In order to make users choose the best matching services and give users with trusted services, the model also takes the similarity between services into account and uses the similarity degree to amend the integration reputation value with harmonic-mean. Finally, the effectiveness and feasibility of this model is illustrated by the experiment.
- H. Ibrahim, P. K. Atrey, and E. S. Abdulmotaleb, “Semantic similarity based trust computation in websites,” International Multimedia Conference, New York, ACM, pp. 65–72, 2007.
- S. K. Chong and J. H. Abawajy, “Feedback credibility issues in trust management systems,” 2007 International Conference on Multimedia and Ubiquitous Engineering: proceedings: MUE’07, Los Alamitos, Calif., IEEE Com-puter Society, pp. 387–391, 2007.
- Donovan J O and Smyth B, “Trust in recommender systems,” in proceedings of the 10th international conference on Intelligent user interfaces, New York, ACM, pp. 167– 174, 2005.
- P. Massa and P. Avesani, “Trust-aware recommender systems,” in proceedings of the 2007 ACM conference on Recommender systems. New York, ACM, pp. 17–24, 2007.
- Y. Gil and D. Artz, “Towards content trust of web resources,” in proceedings of the 15th international conference on World Wide Web, New York, ACM, pp. 565– 574, 2006.
- D. S. Peng, C. Lin, and W. D. Liu, “A distributed trust mechanism directly evaluating reputation of nodes,” Journal of Software, Vol. 19, No. 4, pp. 946–955, April 2008.
- Y. Wang and V. Varadharajan, “Role-based recommendation and trust evaluation,” in the 9th IEEE International Conference on E-Commerce. Technology and the 4th IEEE International Conference on Enterprise Computing, E–Commerce and E–Services, Tokyo, IEEE, pp. 278–288, 2007.
- P. Varalakshmi, S. Thamarai Selvi and M. Pradeep, “A multi-broker trust management framework for resource selection in grid,” in Communication Systems Software and Middleware, COMSWARE’07, 2nd International Conference on Bangalore, IEEE, pp. 7–12 January 2007.
- S. X. Jiang and J. Z. Li, “A reputation–based trust mechanism for p2p e-commerce systems,” Journal of Software, Vol. 18, No. 10, pp. 2551–2563, 2007.
- M. Blaze, J. Feigenbaum, and J. Lacy, “Decentralized trust management,” in proceedings of the 17th Symposium on Security and Privacy, CA, IEEE Computer Society Press, pp. 164–173, 1996.
- C. Lin, L. Q. Tian, and Y. Z. Wang, “Research on user behavior trust in trustworthy network,” Journal of Computer Research and Development, Vol. 45, No. 12, pp. 2033–2043, 2008.
- S. D. Kamvar and M. T. Schlosser, “EigenRep: Reputation management in P2P networks,” in Lawrence S, ed. Proceedings of the 12th International World Wide Web Conference Budapest, ACM Press, pp. 123?134, 2003.