计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (14): 98-102.DOI: 10.3778/j.issn.1002-8331.2010.14.029

• 网络、通信、安全 • 上一篇    下一篇

大规模分布式系统中低通信阈值监控方法

朱幸辉1,张林峰1,田 李2   

  1. 1.湖南农业大学 信息科学技术学院,长沙 410128
    2.国防科技大学 计算机学院,长沙 410073
  • 收稿日期:2008-11-06 修回日期:2009-02-23 出版日期:2010-05-11 发布日期:2010-05-11
  • 通讯作者: 朱幸辉

Communication efficient threshold monitoring method for large-scaled distributed systems

ZHU Xing-hui1,ZHANG Lin-feng1,TIAN Li2   

  1. 1.College of Information Science and Technology,Hunan Agricultural University,Changsha 410128,China
    2.School of Computer Science,National University of Defense Technology,Changsha 410073,China
  • Received:2008-11-06 Revised:2009-02-23 Online:2010-05-11 Published:2010-05-11
  • Contact: ZHU Xing-hui

摘要: 为了进一步降低分布式阈值监控处理中的通信开销,把多个被监控对象作为整体进行统一处理,充分利用对象间的相对关系,提出了一种比分别单独监控更加有效的方法CEM(Communication Efficient Method)。该方法在所有未超过阈值的对象中选择具有最大全局值的对象作为代表,通过调整因子使得代表对象调整后的局部值在每个节点上看来都是最大,因此只需对代表对象进行持续监控即可保证正确性;将多个对象的持续监控变为对代表对象的监控和对局部约束条件的维护操作,当局部约束被打破时,才需要通信并进行参数调整以重建约束。真实数据集上的实验表明,CEM方法能够有效降低分布式阈值监控中的通信开销。

关键词: 分布式系统, 阈值监控, 连续查询, 通信开销

Abstract: The problem of communication reduction over continuous threshold monitoring in distributed systems is considered in this paper.A Communication Efficient Method(CEM) is proposed which utilizes the relationship among objects and processes them as a whole,therefore achieves better performance than those who holding each object separately.In specific,the object with largest value is chosen as the representative object,and adjustment factors are used to guarantee that local value of representative object is also the largest one in each remote node.Therefore,only the representative object needs to be monitored continuously as long as all the local constrains are valid.When local constrain is violated,communication is needed among the coordinator and remote nodes to rebuild the constrain.Experimental evaluation on real data sets show the efficiency of CEM on communication reduction over distributed threshold monitoring.

Key words: distributed system, threshold monitoring, continuous query, communication reduction

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