计算机应用 ›› 2009, Vol. 29 ›› Issue (07): 1861-1864.

• 网络与通信 • 上一篇    下一篇

多用户连续k近邻查询多线程处理技术研究

廖巍1,吴晓平2,严承华3,钟志农4   

  1. 1. 武汉海军工程大学电子工程学院信息安全系
    2. 海军工程大学
    3.
    4. 国防科技大学电子工程学院
  • 收稿日期:2008-12-25 修回日期:2009-02-25 发布日期:2009-07-01 出版日期:2009-07-01
  • 通讯作者: 廖巍
  • 基金资助:

    中国博士后科学基金(No. 20080431384);国家863高技术发展计划(2007AA12Z208);国家级基金

Research on multi-threading processing of concurrent multiple continuous k-nearest neighbor queries

  • Received:2008-12-25 Revised:2009-02-25 Online:2009-07-01 Published:2009-07-01

摘要:

针对面向移动对象集的多用户连续k近邻查询处理,提出了基于多线程的多用户连续查询处理(MPMCQ)框架,采用流水线处理策略,将连续查询处理过程分解为可同时作业的查询预处理、查询执行以及查询结果分发三个执行阶段,利用多线程技术来提高多用户连续查询处理的并行性;基于MPMCQ框架和移动对象内存格网索引,提出了基于多线程的连续k近邻查询处理(MCkNN)算法。实验结果与分析表明,基于MPMCQ框架的MCkNN算法在多核平台上优于CPM、YPK-CNN等现有算法。

关键词: 连续k近邻查询;多核多线程;MPMCQ框架;MCkNN算法;流水线策略

Abstract:

To deal with the multiple concurrent continuous k nearest neighbors queries towards moving objects, the proposed a Multithreading Processing of Multiple Continuous Queries (MPMCQ) framework, which adopted pipeline strategy and departed the continuous query processing into three simultaneous stages: query processing, query executing and query results dispatching to improve the parallelism with multithreading technology. Based on MPMCQ framework and grid index for moving objects, a Multithreading processing of Continuous k Nearest Neighbor queries (MCkNN) algorithm was also presented. Experimental results and analysis show that MCkNN algorithm outperforms CPM, YPK-CNN,etc.

中图分类号: