An Efficient Context Model for Fast Responsiveness of Context-Aware Services in Mobile Networks

In order to provide context-aware services, context modeling is one of the most important tasks. Ontology has been widely accepted for the context modeling but it brings some overheads in the process of reasoning large-scale and dynamic information. In mobile networks, especially, ontology should be verified to be applicable for Context-aware Services since real-time responsiveness for large scale moving users is highly required to be guaranteed. This paper proposes an efficient context model to overcome the limitation of ontology. For the purpose, we design a conceptual context model and compare the processing time of the context-aware mobile service system implying the three different context modeling approaches ontology, database, and proposed hybrid modeling. As the result of performance evaluations, the proposed hybrid model shows faster processing time among them and lesser affected by the major metrics of mobile services changeability and number of users than the two existing models. Based on the experimental results, we expect that the proposed hybrid model is very useful and efficient for fast responsiveness to support Context-aware Services for large scale users in mobile networks.