An adaptive service selection approach in mobile environment

Despite the rapid advances in mobile technology, many constraints still prohibit mobile devices to run resource-demanding applications in mobile environments. Due to the stability of the wireless network, changes of QoS level and user preferences at real-time, how to adaptive choose the "right" service for users is becoming a new challenge. In this paper we present an adaptive service selection algorithm. The algorithm firstly extracts user preferences from services\´ evaluation and calculates the similarity of service with the weighted Euclidean distance then combined with user context data and finally recommends the most appropriate service to the user. In addition, we apply the fuzzy cognitive maps based model to the adaptive policy which improves the efficiency and performance of the algorithm. Finally, the experiment and simulation demonstrate that our approach is effective and available.