Selecting Web Service for Multi-user Based on Multi-QoS Prediction

In this paper, we study a new framework for multi-user Web services selection problem, which aims to select best candidates to meet multi-user's requirements. However, the unavoidable challenges in this problem are the efficiency and effect. Most existing methods are proposed for the single request condition without considering the overload of Web services, which cannot be directly used in this problem. Furthermore, existing methods assumed the QoS information for users are all known and accurate, and in real case, there are always many missing QoS values in history records, which increase the difficulty of the selection. In this paper, we propose a new framework for multi-user Web services selection problem. This framework first predicts the missing multi-QoS values according to the historical QoS experience from different users, and then selects the global optimal solution for multi-user by our fast match approach. Comprehensive empirical studies demonstrate the utility of the proposed method.