摘要
高效地管理移动对象以支持查询是一个重要课题.为了支持在城市交通网络上的移动对象过去、现在和将来位置查询,提出了一种新的索引技术.首先提出基于模拟预测的位置表示模型来改进对移动对象将来运动轨迹的预测精度;其次根据城市交通网的特征,设计了一种全新的动态结构自适应单元(AU),将其开发为一个基于R树的索引结构(current-AU);最后在AU的基础上进行扩展(past-AU)使其支持移动对象历史轨迹查询并且避免了大量的死空间.实验证明,AU索引优于传统的TPR树和TB树索引.
Advance in wireless sensor networks and positioning technologies enable new data management applications that monitor continuous streaming data. In these applications, efficient management of such data is a challenging goal due to the highly dynamic nature of the data and the need for fast, on-line computations. An efficient indexing structure for moving objects is necessary for supporting the query processing of these dynamic data. Existing work can not index the past, current and future positions of moving objects at the same time. In this paper, a novel index technique is proposed to support querying the past, present and future positions of moving objects in urban traffic networks. First, a simulation based location prediction model for the vehicle future trajectory is presented, which is more accurate than the traditional linear prediction model in the TPR-tree. Moreover, exploiting the feature of traffic networks, it presents a dynamic structure termed AU （adaptive unit） and develops it to an R-tree based index named current-AU. Finally, by naturally extending the AU, the past-AU is proposed, which is capable of indexing historical trajectory and at the same time avoiding the dead space that is inevitable in the TB-tree. Experimental studies indicate that the AU-index outperforms the traditional TPR-tree and TB-tree.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2007年第6期1008-1014,共7页
Journal of Computer Research and Development
基金
国家自然科学基金项目(60573091
60273018)
国家"九七三"重点基础研究发展规划基金项目(2003CB317000)
教育部新世纪优秀人才支持计划基金项目
中国人民大学博士学位论文创新资助计划基金项目~~
关键词
移动对象数据库
索引方法
位置模型
交通网络
位置服务
moving object database
indexing method
location model
traffic network
location based service
