Rough Set Model for Prediction of Trustworthy Web Services
The main aim of this paper is to propose a rough set model for predicting the trustworthiness of Web services by the way of ranking them using the estimation of non-functional parameters of each service. The Web services are operating in a distributed environment and hence the ranking of services may not be unique and cannot be predicted precisely. The opinions of the evaluators are sometimes not neutral and quantifying the information will produce an imbalanced result. Rough sets are applied to obtain an effective and unbiased ranking of services using the information provided by the evaluators. The non-functional QoS parameters i.e. reliability, availability, security and integrity of the services are considered as conditional attributes and the reputation of the service represents the decision attribute. To obtain the significance of each QoS parameter, a set of decision rules has been formulated with conditional and decision attributes. The concepts of rough sets based approximation and cardinality are applied to compute the impact (weight) of each attribute in the given data set. Grey relational analysis is applied to normalize the data collected from the evaluators. The rank of the service is determined by computing the weight of the attributes using normalized data and hence the trustworthiness of the Web services has been evaluated.
KeywordsWeb services Rough Set Grey Relational Analysis QoS Trustworthy
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