Rule-based approach for context inconsistency management scheme in ubiquitous computing environments

Abstract

Context-awareness is the key concept that enables smart services to be served in a ubiquitous manner. Context data which represent a user’s situation are updated frequently due to the dynamic changes of the various sensor values and the situations of application entities. Without a proper management, the contexts stored in the system will become different from those of the real-world. The inconsistent contexts will cause context inconsistency problem and make it difficult to provide services in a smart manner. Thus the inconsistent contexts should be eliminated in an appropriate manner. In this thesis, we define what context inconsistency problem is and propose a context inconsistency management scheme based on context elimination rules that describe the semantics of invalid contexts to timely handle inconsistency problems. The proposed scheme enables users to specify deletion conditions for the inconsistent contexts. Our performance evaluation shows that the proposed scheme achieves effective context inconsistency management by eliminating inconsistent contexts as specified in context elimination rules. Also the presumed rule processing overhead for inconsistent context management is compensated by virtue of the well-maintained size of the stored contexts resulting from the proposed scheme.