A Moving Object Query Method Based on the Cache Hit Rate in the Domestic Platform
Pages 169 - 175
Abstract
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.
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Published In
June 2023
354 pages
ISBN:9781450399883
DOI:10.1145/3606043
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Publication History
Published: 16 November 2023
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HP3C 2023
HP3C 2023: 2023 7th International Conference on High Performance Compilation, Computing and Communications
June 17 - 19, 2023
Jinan, China
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