A Moving Object Query Method Based on the Cache Hit Rate in the Domestic Platform

The GPS positioning sensors enable mobile devices to generate amounts of location-based data, such as trajectory, gyro, and GPS data. One meaningful work is efficient querying and managing moving objects. Querying moving objects are widely used in several applications, including shopping centers, tourist attractions, and location-based advertising. Traditional methods search for moving objects without good performance in the long-term moving objects. The strategies for processing moving objects are focused on trajectories. Besides, there is no support for querying the moving objects on the domestic platform. Thus, in this paper, we proposed a novel moving objects model and a new query method based on the cache hit rate in the domestic platform. First, we modeled different moving objects in the PostgreSQL database and designed the type of MPoint, MLineString, MPolygon, Mint, MDouble, etc. Then, we proposed the strategy of segmenting long-term moving objects, to reduce the time of traversals of long-term moving objects. Finally, we built the experiment evaluation by using the BerlinMOD benchmark, we compared our algorithm with SECONDO to verify the performance of the proposed algorithm in terms of query time.