吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (6): 1799-1805.doi: 10.13229/j.cnki.jdxbgxb201406040

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路网移动对象聚集索引技术

冯钧1, 史涯晴1, 2, 唐志贤1, 芮彩华1   

  1. 1.河海大学 计算机与信息学院,南京 210098;
    2.中国人民解放军理工大学 指挥信息系统学院,南京210008
  • 收稿日期:2013-04-27 出版日期:2014-11-01 发布日期:2014-11-01
  • 通讯作者: 史涯晴(1981-),女,讲师,博士研究生.研究方向:时空间信息检索.E-mail:yqshi_nanjing@163.com
  • 作者简介:冯钧(1969-),女,教授,博士生导师.研究方向:时空间信息检索.E-mail:
  • 基金资助:
    国家自然科学基金项目(61370091,61170200); 江苏省科技支撑计划(工业)项目(BE2012179); 江苏省普通高校研究生科研创新计划项目(CXZZ12_0229); 解放军理工大学预先研究基金项目

Aggregation index technique of moving objects in road networks

FENG Jun1, SHI Ya-qing1, 2, TANG Zhi-xian1, RUI Cai-hua1   

  1. 1.College of Computer and Information, Hohai University, Nanjing 210098, China;
    2.Institute of Command Information Systems, PLA University of Science and Technology, Nanjing 210008, China
  • Received:2013-04-27 Online:2014-11-01 Published:2014-11-01

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摘要： 结合能够解决重复计数问题的Sketch技术和能够以较小存储空间获得高效近似聚集查询结果的AMH+技术,借鉴aCN-RB-tree支持方向属性聚集的特性,提出了DSD+动态草图索引结构,解决了路网环境下移动对象的聚集查询问题。性能分析和试验结果表明:与现有的索引结构相比,DSD+在保证查询时间和查询误差优势的基础上显著减少了存储空间。

关键词: 计算机应用, 路网, 聚集查询, 移动对象索引

Abstract: A new index structure, DSD+, which is the dynamic sketch with direction index, is proposed to solve the problem of aggregate query of moving objects in the road network environment. This technique combines the sketch technology, which can solve distinct counting problem, and the AMH+ technology, which can give out efficient approximate aggregate query results with smaller storage space; and utilizes the characteristics of aCN-RB-tree that supports aggregate by the direction property. The performance analysis and the experimental results show that, with the same query time and precision, the query storage space of the proposed DSD+ index structure is less than that of existing index structures.

Key words: computer application, road networks, aggregate query, index of moving objects

中图分类号: 

  • TP39
[1] Papadias D, Tao Y F, Kalnis P, et al. Indexing spatio-temporal data warehouses[C]∥Proceedings of International Conference on Data Engineering. San Jose CA, USA, 2002: 166-175.
[2] Tao Y F, Kollios G, Considine J, et al. Spatio-temporal aggregation using sketches[C]∥Proceedings of International Conference of Data Engineering, Boston, USA,2004: 214-226.
[3] Odysseas P, Minos G, Antonios D. Sketch-based querying of distributed sliding-window data streams[C]∥Proceedings of the VLDB Endowment,Istanbul, Turkey, 2012: 992-1003.
[4] Sun J M, Papadias D, Tao Y F, et al. Querying about the past,the present, and the future in spatio-temporal[C]∥Proceedings of International Conference of Data Engineering, Boston, USA,2004:202-213.
[5] Feng Jun, Lu Ja-min, Lu Yang, et al. RR-tree: an efficient structure for managing road networks[C]∥Proceedings of the 16th International Conference on Applications of Declarative Programming and Knowledge Management, Japan, 2005:107-116.
[6] Feng Jun, Lu Chun-yan, Wang Ying, et al. Sketch RR-tree:a spatio-temporal aggregation index for network-constrained moving objects[C]∥Proceedings of International Conference on Innovative Computing, Information and Control, Dalian,China,2008:4-7.
[7] Jin Che-qing, Guo Wei-bin, Zhao Fu-tong. Getting qualified answers for aggregate queries in spatio-temporal databases[J]. Lecture Notes in Computer Science,2007,4505:220-227.
[8] Feng Jun, Zhu Zhong-hua. Modified histogram: a spatio-temporal aggregate index for moving objects in road networks[J]. Procedia Engineering, 2012,29:4135-4139.
[9] Frentzos E. Indexing objects moving on fixed networks[C]∥Proc 8th International Symposium on Spatial and Temporal Databases, Santorini Island, Greece, 2003:289-305.
[10] Nguyen T, He Z, Zhang R, et al. Boosting moving object indexing through velocity partitioning[C]∥Proceedings of the VLDB Endowment, Istanbul, Turkey,2012:860-871.
[11] Lee D W, Baek S H, Bae H Y. aCN-RB-tree: update method for spatio temporal aggregation of moveing object trajectory in ubiquitous environment[C]∥International Conference on Computational Science and Its Application, Korea, 2009:177-182.
[12] Philippe F, Nigel M G. Probabilistic counting algorithms for data base applications[J]. JCSS, 1985,32(2):182-209.
[13] Ding Xiao-feng, Lian Xiang,Chen Lei, et al. Continuous monitoring of skylines over uncertain data streams[J]. Information Science, 2012,184(1):196-214.
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