No abstract

No abstract

No abstract

Community of web services (CWS) is a society composed by a number of functionally identical web services. The communities always aim to increase their reputation level in order to obtain more requests. In this paper, we propose an effective mechanism dealing with reputation assessment for communities of web services. The proposed mechanism is based on after-service feedbacks provided by the users to a run-time logging system. The proposed method defines the evaluation metrics involved in reputation assessment of a community, and supervises the logging system in order to verify the validity and soundness of the feedbacks provided by the users. In this paper, the proposed framework is described, a theoretical analysis of its assessment and its implementation along with empirical result discussions are provided. We also show how our model is efficient, particularly in very dynamic environments.

This paper aims to propose an effective mechanism dealing with reputation assessment of communities of web services (CWSs) that are known as societies composed by a number of functionally identical web services. The objective is to provide a general incentive for CWSs to act truthfully given that they are allowed to decide about their actions.The considered entities (web services, virtual organizations, etc.) 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. 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, which allows the controller agent to keep the logging file accurate. The proposed framework defines the evaluation metrics involved in the reputation assessment of a community, and supervises the logging system in order to verify the validity and soundness of the feedback provided by the users. 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. We also show how our model is efficient, particularly in very dynamic environments.