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趋势.
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.