arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1308.2002cs.NI
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P2P网络路由拓扑推理的搭便车算法

Taking A Free Ride for Routing Topology Inference in Peer-to-Peer Networks

Peng Qin, Bin Dai, Kui Wu, Benxiong Huang, Guan Xu

摘要:

对等(P2P)网络中,如果节点提供底层网络层路由拓扑结构,可以提高其性能。推断从一台终端主机到一组其他主机的网络层路由拓扑和链路性能的任务被称为网络断层扫描,它通常需要主机发送探测消息。我们设计了一种被动的网络断层扫描方法,不需要任何探测消息,并采取免费乘坐的数据流在P2P网络。它基于端到端时延相关估计(DCE)来推断路由拓扑,而不需要中间路由器的任何同步或合作。我们在真实的互联网环境中实现并测试了我们的方法,并取得了92%的准确率在拓扑恢复。我们还在OMNet++中进行了大量的仿真,以评估其在大规模网络上的性能,表明其拓扑恢复准确率约为95%。

英文摘要:

A Peer-to-Peer (P2P) network can boost its performance if peers are provided with underlying network-layer routing topology. The task of inferring the network-layer routing topology and link performance from an end host to a set of other hosts is termed as network tomography, and it normally requires host computers to send probing messages. We design a passive network tomography method that does not requires any probing messages and takes a free ride over data flows in P2P networks. It infers routing topology based on end-to-end delay correlation estimation (DCE) without requiring any synchronization or cooperation from the intermediate routers. We implement and test our method in the real world Internet environment and achieved the accuracy of 92% in topology recovery. We also perform extensive simulation in OMNet++ to evaluate its performance over large scale networks, showing that its topology recovery accuracy is about 95% for large networks.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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