MAD-RAPPEL: Mobility Aware Data Replacement And Prefetching Policy Enrooted LBS - Ajay K. Gupta; Udai Shanker (Journal of King Saud University: Computer and Information Sciences)
The features of mobile devices are being continuously upgraded to provide quality of services to the mobile user seeking location-based information by allowing the usage of context-aware data. To protect an individual’s location & his information to untrusted entity, a multi-level caching, i.e., Mobility Aware Data Replacement & Prefetching Policy Enrooted LBS using spatial k-anonymity (MAD-RAPPEL) is being proposed in this paper. It enhances user privacy by forming the cloaking region in cache replacement and prefetching. The cache replacement and invalidation module uses the next location prediction algorithm by the application of the mobility Markov model on mobile user’s trajectories. The client-server queuing model is used to simulate the system for the experimentation to see the performance of MAD-RAPPEL. The results obtained through the simulation demonstrate that the proposed MAD-RAPPEL minimizes the overhead of the LBS as compared to already existing prior LBSs.