Applications ranging from location-based services to multi-player online gaming require continuous query support to monitor, track, and detect events of interest among sets of moving objects. Examples are alerting capabilities for detecting whether the distance, the travel cost, or the travel time among a set of moving objects exceeds a threshold. These types of queries are driven by continuous streams of location updates, simultaneously evaluated over many queries.
In this paper, we define three types of proximity relations that induce location constraints to model continuous spatio-temporal queries among sets of moving objects in road networks. Our focus lies on evaluating a large number of continuous queries simultaneously. We introduce a novel moving object indexing technique that together with a novel road network partitioning scheme restricts computations within the partial road network. These techniques reduce query processing overhead by more than 95%. Experiments over real-world data sets show that our approach is twenty times faster than a baseline algorithm.
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