Historic and clustering based QoS aggregation for composite services

Abstract

Web services run in an open, heterogeneous and multi-tenant network environment, which makes the QoS of services uncertain and difficult to be described by a known probability distribution. Therefore, the calculation of QoS aggregation for composite services is facing challenges. This paper presents a new method for the aggregation calculation of composite services. In this method, the QoS of Web services is characterized by the sample space formed by their historical records, and a clustering method is adopted to control the number of samples in the sample space, so as to avoid the problem of combinatorial explosion during the process of aggregation calculation. This method does not need to limit the distribution of QoS, and is suitable for the composite services described by various common workflows and all kinds of QoS attributes. Experiments show that our method has advantages in terms of time cost and computational accuracy compared with the existing methods.