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Taking a free ride for routing topology inference in peer-to-peer networks

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Abstract

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 require 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.

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Notes

  1. Rooted from a single source node, the network-layer routing structure to multiple destination nodes is always a tree structure at any given time instance, or otherwise routing loops exist.

  2. We argue that passive network tomography using RTT measurement is problematic in P2P networks for at least two reasons: first, message delivery between peers may not use TCP, and thus we cannot use TCP-SYN and TCP-ACK for passive RTT estimation as in [17]; second, even if passive RTT estimation is possible, the correlation estimation of the return paths is hard due to the variable processing delay at the destination nodes.

  3. This implies that the sender have data to both receivers. This assumption is reasonable due to the diverse data forwarding requirements in P2P networks. Otherwise, passive network tomography will not have enough information to accurately infer routing topology.

  4. For simplicity we usually choose the root node as the base router. However, in fact any intermediate node can be selected as the base router since the dynamic algorithm can go both directions in different cases within a tree.

  5. A slice is a set of allocated resources distributed across PlanetLab. Slice is implemented using a technique called distributed virtualization. After nodes have been assigned to a slice, virtual servers for that slice are created on each of the assigned nodes.

  6. Waxman refers to a generation model for a random topology using Waxman’s probability model for interconnecting the nodes.

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Acknowledgments

This work was supported by the National Key Technology Research and Development Program of the Ministry of Science and Technology of China under Grant no. 2012BAH93F01, the Innovation Research Fund of Huazhong University of Science and Technology, no. 2014TS095, the National Science Foundation of China under Grant no. 60803005, the National Science Foundation of China under Grant no. 91338201 and the Grand Foundational Research Program of China (863 Program) under Grand no.2015AA015701.

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Authors and Affiliations

  1. School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China

    Peng Qin, Bin Dai, Guan Xu & Benxiong Huang

  2. Department of Computer Science, University of Victoria, Victoria, Canada

    Peng Qin & Kui Wu

  3. China Academy of Electronics and Information Technology, Beijing, China

    Peng Qin

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  1. Peng Qin
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  2. Bin Dai
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  5. Benxiong Huang
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Correspondence to Bin Dai.

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Qin, P., Dai, B., Xu, G. et al. Taking a free ride for routing topology inference in peer-to-peer networks. Peer-to-Peer Netw. Appl. 9, 1047–1059 (2016). https://doi.org/10.1007/s12083-015-0380-9

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