Abstract
In modern distributed systems, service consumers are faced with pools of service providers that offer similar functionalities. This reality renders the selection of web services a challenging task. One popular solution is to base the selection decisions on the web services' non-functional requirements depicted by a variety of QoS metrics. In this paper, we present a new approach for solving the web service selection problem; a QoS-aware trust model that leverages the correlation information among various QoS metrics. This model, based on the probability theory, estimates the trustworthiness of web services by exploiting two statistical distributions, namely, Dirichlet and generalized Dirichlet. These distributions represent the outcomes of multiple correlated QoS metrics. The former distribution is employed when the QoS metrics are positively correlated while the latter handles negatively correlated metrics. We also propose an algorithm to aggregate reputation feedback that propagate among the interacting web services. This algorithm deals with malicious feedback and various strategic behavior commonly performed by web services. Experimental results endorse the advantageous capability of our trust model and reputation algorithm compared to the state-of-the-art.
Original language | British English |
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Pages (from-to) | 968-981 |
Number of pages | 14 |
Journal | IEEE Transactions on Services Computing |
Volume | 9 |
Issue number | 6 |
DOIs | |
State | Published - 1 Nov 2016 |
Keywords
- generalized Dirichlet
- probabilistic models
- QoS
- reputation
- trust