网络距离预测技术研究
DOI:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

Supported by the National Natural Science Foundation of China under Grant Nos.60621003, 60873215 (国家自然科学基金); the National Basic Research Program of China under Grant No.2005CB321801 (国家重点基础研究发展计划(973)); the Foundation for the Author of National Excellent Doctoral Dissertation of China under Grant No.200141 (高等学校全国优秀博士学位论文作者专项)


Network Distance Prediction Technology Research
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    P2P网络中节点间的距离信息是实现拓扑感知以优化覆盖网应用以及解决网络监管等问题的基础. P2P网络的大规模、自组织、高度动态等复杂特征使得要准确、完全地测量节点间的距离信息面临着极大的困难.因此,研究者们提出各种预测技术,目前对网络距离预测技术的研究已成为P2P领域的研究热点.首先,提出了一个网络距离预测技术的研究框架,指出了研究的重点以及相关技术问题,分析了研究历史;其次,对各种预测方法加以分类,在分类的基础上,介绍了各种典型的预测方法并进行了对比分析;最后总结了各种精确性度量标准,并指出了未来的研究

    Abstract:

    The distance information between nodes in P2P network is the basis for achieving topology-awareness which aims at optimizing the applications of overlay and solving the problems such as network monitoring. However, it seems infeasible to accurately and completely measure the distances between nodes due to the characteristics of P2P, such as being large-scale, self-organized, highly dynamic and so on. Consequently, researchers have put forward various prediction methods, and currently the network distance prediction technology is emerging as a new hotspot of research in P2P area. Firstly, a research framework is proposed, based on which the main aspects and the related technical issues of the research are analyzed. Meanwhile, the research history and the analysis of the classification are investigated. Many typical methods are introduced and compared. Lastly, the metrics of precision, as well as future research trends of network distance prediction is reviewed.

    参考文献
    相似文献
    引证文献
引用本文

王意洁,李小勇.网络距离预测技术研究.软件学报,2009,20(6):1574-1590

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2008-07-02
  • 最后修改日期:2008-11-17
  • 录用日期:
  • 在线发布日期:
  • 出版日期:
文章二维码
您是第位访问者
版权所有:中国科学院软件研究所 京ICP备05046678号-3
地址:北京市海淀区中关村南四街4号,邮政编码:100190
电话:010-62562563 传真:010-62562533 Email:jos@iscas.ac.cn
技术支持:北京勤云科技发展有限公司

京公网安备 11040202500063号