MOQ-QR:基于QR-树的连续K近邻查询算法研究*

综合分析了R-树和四叉树在处理移动对象的连续K近邻（简称CKNN）查询算法中的不足，提出了一种基于R树和四叉树索引结构，去解决移动对象连续K近邻查询算法。该算法通过对移动对象分配静态空间，并在研究区域内利用QR-树和hash表作为索引去存储移动对象以此计算查询点与移动对象之间的空间距离。实验证明，该算法与现有算法相比，不仅提高了数据的查询效率，而且降低了系统资源的消耗。

MOQ-QR:query processing research for CKNN based on QR-tree

This paper comprehensively analyzed the deficiencies of continuous K-nearest neighbor (CKNN for short) query processing on R-tree and quad tree.It proposed a new index structure called MOQ-QR based on R-tree and quad tree(QR tree),which could solve CKNN query processing of moving objects.Calculated the distances between the query point and moving objects by allocating a static space to the moving objects, and making use of QR-tree and hash tables as an index to store the moving object.Experimental results show that, compared with the existent processing algortihms, the proposed algorithm not only improves the query efficiency, but also reduces the consumption of the system resource.