A fuzzy service adaptation engine for context-aware mobile computing middleware

Purpose – Context-aware mobile computing extends the horizons of the conventional computing model to a ubiquitous computing environment that serves users at anytime, anywhere. To achieve this, mobile applications need to adapt their behaviors to the changing context. The purpose of this paper is to present a generalized adaptive middleware infrastructure for context-aware computing. Design/methodology/approach – Owing to the vague nature of context and uncertainty in context aggregation for making adaptation decisions, the paper proposes a fuzzy-based service adaptation model (FSAM) to improve the generality and effectiveness of service adaptation using fuzzy theory. Findings – By the means of fuzzification of the context and measuring the fitness degree between the current context and the predefined optimal context, FSAM selects the most suitable policy to adopt for the most appropriate service. The paper evaluates the middleware together with the FSAM inference engine by using a Campus Assistant application. Originality/value – The paper is of value in presenting a generalized adaptive middleware infrastructure for context-aware computing and also comparing the performance of the fuzzy-based solution with a conventional threshold-based approach for context-aware adaptation.