Dynamic QoS Data-driven Reliable Web Service Selection
Longchang Zhang, Yan-Hong Yang · 2016
The optimal Web service selection based on QoS is still a hot issue. Highly dynamic QoS data leading to uncertainty QoS model is a huge challenge for reliable Web service selection. This paper presents Dynamic QoS Data-driven Reliable Web Service Selection (DQoS_RSS). First, DQoS_RSS uses mean and standard deviation to portray the benefit and risk of QoS and to improve the accuracy of QoS description. Then, the uncertain service Skyline set is built to reduce the search scope, to improve the efficiency of Web service selection. Drown on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) theory, 2 kinds of service selection algorithm are designed to obtain the optimal Web service reflecting user's QoS needs. In addition, 2 kinds of QoS model converter are introduced to convert QoS data to QoS model; and the QoS model adaptive adjustment mechanism is introduced too, which can adapt to the dynamic changes of QoS. Finally, some experiments demonstrate the superiority and efficiency of the presented approach.