Service adaptation using fuzzy theory in context-aware mobile computing middleware

Abstract

Context-aware mobile computing middleware is designed to automatically adapt its behavior to changing environment. To achieve this, an important issue to be addressed is how to effectively select services for adaptation according to the user's current context. Existing work does not adequately address this issue. In this paper, we propose a Fuzzy-based Service Adaptation Model (FSAM) that can be used in context-aware middleware. We formulate the service adaptation process by using fuzzy linguistic variables and membership degrees to define the context situations and the rules for adopting the policies of implementing a service. We propose three fitness functions to calculate the fitness degree for each policy based on the distance of fuzzy status between the policy and the current context situation. The decision for service adaptation is achieved by selecting the policy with the largest fitness degree. A context-aware application scenario called Campus Assistant is used to exemplify the proposed service adaptation process and demonstrate its effectiveness.