CUU:大规模时空数据区域查询更新策略

CUU:A Solution for Range Query and Update on Large-Scale Spatial-Temporal Data

移动终端的普及催生了海量的时空数据。由于有了数据基础的支持,基于位置的服务应用也随之普及。传统的时空数据存储方案既难以适用于存储规模庞大、频繁更新的数据,又很难提供并发、高精度的区域查询服务。因此,参考大规模时空数据并发查询更新问题领域的最新研究成果,分析了该领域主流算法的特点及缺陷,设计了适用于海量高更新频率的时空数据(移动通信数据)的查询与更新算法CUU,讨论了区域查询精度问题及其解决方案。在真实移动通信数据上的实验结果表明,CUU算法可以高效处理并发的时空数据查询与更新。

As the mobile terminals are more and more widely used, large-scale spatial-temporal data are being created. Large-scale spatial-temporal data have made location based service popular. Traditional spatial-temporal indexes arenot capable of storing large-scale and frequently updated data and at the same time providing concurrent high resolu- tion range query. This paper explores latest research productions on solving concurrent updating and queries on large-scale spatial-temporal data, and analyzes the characters and weaknesses of mainstream algorithms. Then this paper presents a new algorithm called CUU on solving storing, updating and queries on large-scale spatial-temporal data. It also talks about the accuracy of range query problem and its solution. The experimental results on real tele- communication data show that CUU is capable of offering efficient concurrent queries and update services.