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Analyzing Communities of Web Services Using Incentives

Babak Khosravifar, Jamal Bentahar, Ahmad Moazin, Philippe Thiran

Source Title: International Journal of Web Services Research (IJWSR)7(3)

ISSN: 1545-7362|EISSN: 1546-5004|EISBN13: 9781609609108|DOI: 10.4018/jwsr.2010070102

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MLA

Khosravifar, Babak, et al. "Analyzing Communities of Web Services Using Incentives." IJWSR vol.7, no.3 2010: pp.30-51. http://doi.org/10.4018/jwsr.2010070102

APA

Khosravifar, B., Bentahar, J., Moazin, A., & Thiran, P. (2010). Analyzing Communities of Web Services Using Incentives. International Journal of Web Services Research (IJWSR), 7(3), 30-51. http://doi.org/10.4018/jwsr.2010070102

Chicago

Khosravifar, Babak, et al. "Analyzing Communities of Web Services Using Incentives," International Journal of Web Services Research (IJWSR) 7, no.3: 30-51. http://doi.org/10.4018/jwsr.2010070102

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Abstract

This paper proposes an effective mechanism dealing with reputation assessment of communities of web services (CWSs) known as societies composed of a number of functionally identical web services. The objective is to provide a general incentive for CWSs to act truthfully. The considered entities are designed as software autonomous agents equipped with advanced communication and reasoning capabilities. User agents request CWSs for services and accordingly rate their satisfactions about the received quality and community responsiveness. The strategies taken by different parties are private to individual agents, and the logging file that collects feedback is investigated by a controller agent. Furthermore, the accurate reputation assessment is achieved by maintaining a sound logging mechanism. To this end, the incentives for CWSs to act truthfully are investigated and analyzed, while the proposed framework defines the evaluation metrics involved in the reputation assessment of a community. In this paper, the proposed framework is described, a theoretical analysis of its assessment and its implementation along with discussion of empirical results are provided. Finally, the authors show how their model is efficient, particularly in very dynamic environments.

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Analyzing Communities of Web Services Using Incentives

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