A fuzzy-based service adaptation middleware for context-aware computing

In a mobile environment, it is desirable for mobile applications to adapt their behaviors to the changing context. However, adaptation mechanism may emphasize more on overall system performance, while neglecting the needs of individual. We present a generalized Adaptive Middleware Infrastructure (AMI) to cater for individual needs in a fair manner, while maintaining optimal system performance. Furthermore, due to the vagueness in context nature and uncertainty in context aggregation for adaptation, we propose a Fuzzy-based Service Adaptation Model (FSAM) to achieve generality and improve the effectiveness of service adaptation. By fuzzification of the context and measuring the fitness degree between the current context and the optimal situation, FSAM adopts the most appropriate service. We have evaluated the FSAM inference engine within the middleware AMI by an application Campus Assistant. The performance is analyzed and compared with a conventional threshold-based approach