An Approach to Incentive-Based Reputation for Communities of Web Services

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.

Analyzing Communities vs. Single Agent-Based Web Services: Trust Perspectives

“…In this section, we introduce the reputation model, which is inspired by the one proposed in [6]. We discuss about the opportunities that a CWS offers over single Web services with respect to reputation-model parameters.…”

Game-Theoretic Analysis of a Web Services Collaborative Mechanism

“…In [4], authors propose a reputation-based architecture for communities and investigate the collusion scenarios that might falsely increase communities' reputation in the network. In [5], the authors mainly address the overall assessed reputation that is used as a main reason for service selection. The authors do not consider truth/lie telling analysis as a factor impacting service selection.…”

“…This means web services can be used without worrying about how they are implemented or where in the world they are hosted. As in [4,5] and [8], we abstract web services as rational intelligent agents, which are benefit maximizers. In our framework, the goal of these agents is to receive user requests and satisfy them the best they can.…”

Analyzing the Relationships between some Parameters of Web Services Reputation

“…However, they do not investigate the cases where the community is initiated. In [7], [8], the authors mainly address the overall assessed reputation that is used as a main reason for service selection. The authors do not consider handling as a parameter that impacts service selection in future.…”

“…Therefore, a rational agent acting as the intelligent structure of the Web service would need to analyze the cases where such situations would take place in order to predict their occurrences. One clue would be gathering Web services to build a collaborative virtual group called community that aims to increase Web services' capabilities [8].…”