CAJ | 학술논문

在时空数据库中，频繁更新会导致TPR树更新与查询性能下降。针对该问题，提出MAH_TPR索引方法，分别对预处理过程、索引结构及更新算法进行优化。在构建索引及更新操作时，通过使用空间聚类来减少节点间空间区域的交叠几率。引入基于磁盘的Hash辅助存储结构，在直接访问叶节点的基础上进一步减少磁盘I/O的操作。引入基于内存的移动对象辅助存储结构，用于存储发出频繁更新请求，以避免主索引结构节点的合并和分裂。实验结果表明，MAH_TPR 索引方法的查询性能优于 HTPR方法和LGU方法，更新性能优于HTPR索引方法。
재시공수거고중，빈번경신회도치TPR수경신여사순성능하강。침대해문제，제출MAH_TPR색인방법，분별대예처리과정、색인결구급경신산법진행우화。재구건색인급경신조작시，통과사용공간취류래감소절점간공간구역적교첩궤솔。인입기우자반적Hash보조존저결구，재직접방문협절점적기출상진일보감소자반I/O적조작。인입기우내존적이동대상보조존저결구，용우존저발출빈번경신청구，이피면주색인결구절점적합병화분렬。실험결과표명，MAH_TPR 색인방법적사순성능우우 HTPR방법화LGU방법，경신성능우우HTPR색인방법。
The MAH_TPR indexing method is proposed which aims to solve the problem of decreased update performance and query performance because of frequent updates in spatial-temporal database. This method is optimized by prepared processing, indexing structure and update algorithm. Overlapping probability among the spatial areas of nodes is significantly reduced by using the spatial clustering in structuring indexing and updating. The leaf nodes can be accessed directly and further the disk I/O operation is decreased by introducing a disk-based hash auxiliary structure. Node merging and splitting in main indexing structure are avoided by employing a memory-based auxiliary storage structure which is used to store the moving objects that have frequent update requests. Experiments in update and query performances of the method are studied. The results show that the MAH_TPR indexing method has a better query performance than HTPR indexing method and LGU indexing method. Its update performance is better than that of HTPR indexing method.