A Data Frame Based Spatiotemporal Indexing Algorithm for Moving Objects

With the increasing number of location based services (LBS) and GPS-enabled devices, there are more and more Web based GPS trajectory applications. Since the huge volume of spatiotemporal trajectory data brings about heavy burden for data storing and querying, it is of great importance to organize the trajectory data efficiently to satisfy the indexing demand of many LBS applications. Traditional methods in spatiotemporal database always incur a data search in a large range while users query about trajectories in a particular spatiotemporal region in Web based applications. In this paper, we develop a data frame based spatiotemporal indexing algorithm for moving objects, which is aimed to achieve high efficiency in spatiotemporal retrieval for trajectories. The method first allocates points from different objects of the same timestamp into the identical data frame to construct temporal index. Then it partitions the frames into groups, each group starts with a static frame followed by several dynamic frames. Finally, the method divides the space into blocks based on Geohash algorithm. In this way, temporal and spatial index are combined to achieve high efficiency during the trajectory retrieval. Experiments on real large scale trajectory datasets demonstrate that the proposed algorithm has superiority over traditional methods in speeding up the spatiotemporal retrieval and is quite qualified to the characteristics of Web based LBS applications.