| Summary: | 碩士 === 國立成功大學 === 資訊工程學系碩博士班 === 97 === Efficient processing the spatio-temporal queries over moving objects with uncertain location has become imperative in recent years due to the increasing need for real-time information in highly dynamic environments. In this thesis, we investigate how to process three important types of spatio-temporal queries. They are range query, K-nearest neighbor query, and spatial join query. Most of the existing approaches focus on designing an index structure for managing moving objects with uncertainty, and then utilize it to improve the query performance. All the proposed indexes, however, have some serious shortcomings (such as the high index update cost or the low pruning ability) which limit their improvement in processing the spatio-temporal queries. Therefore, we devote to developing a novel and efficient index, named possible region index (PRI), to index moving objects with uncertainty. By exploiting a well-designed location update strategy,
the PRI needs not be updated frequently. Moreover, it can achieve better query performance than the existing indexes.
Comprehensive experiments demonstrate the efficiency of the PRI in terms of the update cost and the query performance.
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