Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings

Research Article

Probability-Based Routing Symmetry Metrics

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  • @INPROCEEDINGS{10.1007/978-3-030-00557-3_37,
        author={Qin Wang and Fang Dong and Xin-Li Yang and Rui Yin},
        title={Probability-Based Routing Symmetry Metrics},
        proceedings={Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings},
        proceedings_a={MLICOM},
        year={2018},
        month={10},
        keywords={Routing symmetry Routing behavior model Statistical process},
        doi={10.1007/978-3-030-00557-3_37}
    }
    
  • Qin Wang
    Fang Dong
    Xin-Li Yang
    Rui Yin
    Year: 2018
    Probability-Based Routing Symmetry Metrics
    MLICOM
    Springer
    DOI: 10.1007/978-3-030-00557-3_37
Qin Wang1,*, Fang Dong2,*, Xin-Li Yang3,*, Rui Yin2,*
  • 1: China University Program, Texas Instruments Semiconductor Technologies (Shanghai)
  • 2: Zhejiang University City College
  • 3: Port Management Office of Haiyan County
*Contact email: qin-wang@ti.com, dongf@zucc.edu.cn, hyhangyun@163.com, yinrui@zucc.edu.cn

Abstract

In communication networks, if streams between two endpoints follow the same physical paths for both forward and reverse direction, they are symmetric. Routing asymmetry affects several protocols, and impacts part of traffic analysis techniques. We propose two routing symmetry metrics to express different meanings when talking about routing symmetry, namely, (1) the forward and reverse flows coming from one node to another are exactly the same, and (2) one single node is visited by both flows. The two metrics are termed as identity symmetry and cross symmetry, respectively. Then, we build a model to link the macroscopic symmetry with the microscopic routing behavior, and present some analysis results, thus make it possible to design a routing algorithm with some desired symmetry. The simulation and dataset study show that routing algorithms that generate next hop randomly will lead to a symmetric network, but it is not the case for Internet. Because the paths of Internet are heavily dominated by a small number of prevalent routes, Internet is highly asymmetry.