位置不确定性是移动对象的重要特点之一。已有的不确定移动对象索引技术旨在提高查询效率，但是当移动对象位置频繁更新时，存在更新代价较大的问题。针对移动对象频繁位置更新引起的开销增加问题，在TPU-tree索引结构上支持移动对象群组划分策略，给出了一种适用于频繁位置更新的索引结构GTPU-tree。在此基础上提出了基于空间轨迹相似度的群组划分算法STSG（spatial trajectory of similarity group）和不确定移动对象群组更新算法。GTPU-tree通过减少同一分组中移动对象的更新次数，降低磁盘I/O次数，从而降低更新代价。通过实验对基于GTPU-tree和TPU2M-tree等索引结构的算法效率进行了对比分析，结果表明GTPU-tree相比于TPU2M-tree在移动对象数量较大时，GTPU-tree的更新代价将低于TPU2M-tree；与TPU-tree相比插入性能提高约30%，更新代价降低约35%。%Positional uncertainty is one key feature of the moving objects. Existing uncertain moving objects indexing technology aims to improve the efficiency of querying. However, when moving objects��positions update frequently, the update cost is huge. In order to solve this cost problem, this paper modifies the group partition strategy of TPU-tree and gives an index structure named GTPU-tree that supports frequent position update. Furthermore, this paper proposes a group partition algorithm STSG based on spatial trajectory of similarity and moving objects group updating algo-rithm. GTPU-tree reduces the number of disk I/O by reducing the update number in the same group, thus decreasing the update cost. This paper compares and analyzes the algorithm efficiency of GTPU-tree and TPU2M-tree. The exper-imental results demonstrate that while the number of moving objects is large, GTPU-tree update cost will be lower than TPU2M-tree;Compared with TPU-tree, GTPU-tree performs better than TPU-tree, which improves the inserting performance by 30%and reduces the update cost by 35%.
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