OMCPR: Optimal Mobility Aware Cache Data Pre-fetching and Replacement Policy Using Spatial K-Anonymity for LBS

Abstract

Location-based services are an important category of context-aware computing, which play an important role in providing the continuous, local and spatially confined information systems very efficiently and accurately to their clients. The key component in location-based services is the current location of a mobile user. Thus, to protect mobile users’ location and their other information to an untrusted party with consideration of minimal waiting time, Optimal Mobility Aware Cache data Pre-fetching and Replacement policy (OMCPR) is being proposed here. In this continuous location-based services model, the system introduces a mediator namely Anonymizer by employing the prefetching facility for spatial K-anonymity that resides in between the user and Query Analyser to form a cloaking region using mobile user inputs (data freshness, the contribution rate of cell’s cache and location). It provides high-quality lossless location-based services by the utilization of the frequent pattern mining of mobile users’ trajectories to forecast their next position as per mobility and multiple constraints. A client–server based queueing model is used to simulate the proposed OMCPR platform. It provides higher privacy protection than the current state of the art strategies available, also minimizes the overhead of the LBS server and waiting time of mobile users by the addition of the prefetching facilities to Anonymizer.