Reasoning about Context in Uncertain Pervasive Computing Environments
EuroSSC '08 Proceedings of the 3rd European Conference on Smart Sensing and Context
Context-aware adaptive data stream mining
Intelligent Data Analysis - Knowledge Discovery from Data Streams
Probabilistic-constrained fuzzy logic for situation modeling
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Interoperable and adaptive fuzzy services for ambient intelligence applications
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
A fuzzy-based service adaptation middleware for context-aware computing
EUC'06 Proceedings of the 2006 international conference on Embedded and Ubiquitous Computing
Situation-Aware adaptive visualization for sensory data stream mining
Sensor-KDD'08 Proceedings of the Second international conference on Knowledge Discovery from Sensor Data
Dynamic context-aware and limited resources-aware service adaptation for pervasive computing
Advances in Software Engineering
An adaptive rule-based approach for managing situation-awareness
Expert Systems with Applications: An International Journal
Context Inference Engine (CiE): Inferring Context
International Journal of Advanced Pervasive and Ubiquitous Computing
International Journal of Advanced Pervasive and Ubiquitous Computing
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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驴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.