Scaling Spatial Alarm Services on Road Networks

Spatial alarm services are essential components of many location-based applications. One of the key technical challenges for supporting spatial alarms as a service is performance and scalability. This paper shows that the Euclidean distance-based spatial alarm processing techniques are inadequate for mobile users traveling on road networks due to the high overhead in terms of server load for alarm checks and the high energy consumption in terms of client wakeups. We design and develop RoadAlarm, a road network aware spatial alarm processing service, with three unique features. First, we introduce the concept of road network-based spatial alarms using road network distance measures and a set of metrics specialized for spatial alarm processing. Second, we develop the basic model for spatial alarm processing by exploiting two types of filters: subscription filter and Euclidean lower bound filter. Third and but not the least, we develop a suite of optimization techniques to further reduce the frequency of wakeups at mobile clients and the number of alarm checks at the alarm processing server, while ensuring high accuracy of spatial alarm processing. Our experimental results show that RoadAlarm outperforms existing Euclidean space-based approaches with high success rate (accuracy) and significantly increased hibernation time.