Safe Region Techniques for Fast Spatial Alarm Evaluation

Abstract

Spatial alarms are personalized location-based triggers installed by mobile users to serve as a reminder of a location of interest to be encountered in their future trips. Unlike continuous spatial queries, spatial alarms do not require immediate processing and periodic reevaluation upon installation. Thus, a critical challenge for efficient processing of spatial alarms is to determine when to evaluate each spatial alarm, while ensuring the demanding requirements of high accuracy and system scalability. In this paper, we compare alternative approaches for evaluation of spatial alarms: periodic evaluation, safe period-based processing and safe region-based processing. We argue that the safe region-based approach provides highly efficient processing of spatial alarms at the server. Furthermore, it reduces wireless communication costs and energy consumption on the client side by reducing the number of location updates to be transmitted to the server without sacrificing accuracy of spatial alarm evaluation. We develop safe region computation techniques based on different heuristics, namely, Maximum Perimeter Rectangular Safe Region (MPSR), Largest Component Rectangles Safe Region (LCSR) and Bitmap Encoded Safe Region (BSR) approach, and present an in-depth study on trade-offs involved in the selection of an appropriate safe region computation strategy. Our experimental evaluation shows that the best optimization strategy requires an approach which adapts to changing system load conditions and resource constraints, as none of the safe region computation techniques outperforms the others on all relevant evaluation metrics. Experimental evaluation also validates our conjecture that safe region-based processing offers close to optimal performance in terms of CPU load on the server and wireless communication costs at the mobile clients.