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Speeding Up Multi-level Route Analysis Through Improved Multi-LCS Algorithm

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Testbeds and Research Infrastructure: Development of Networks and Communities (TridentCom 2014)

Abstract

Although the multi-level route analysis (e.g., AS, subnet, IP levels) is very useful to many applications (e.g. profiling route changes, designing efficient route-tracing algorithms, etc.), few research investigates how to conduct such analysis efficiently. Regarding routes as sequences, current approaches only handle two routes at a time and they just apply algorithms designed for general sequence comparison. In this paper, we propose and implement a new approach named Fast-rtd that contrasts multiple routes simultaneously and exploits the unique features of Internet routes to decrease the computational complexity in terms of time and memory. Our extensive evaluations on real traceroute data demonstrate the efficiency of Fast-rtd, such as more than 45% memory reduction, 3% to 15% pruning rate increase, and up to 25% speed improvement.

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Correspondence to Weigang Wu .

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© 2014 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Tu, P., Luo, X., Wu, W., Tang, Y. (2014). Speeding Up Multi-level Route Analysis Through Improved Multi-LCS Algorithm. In: Leung, V., Chen, M., Wan, J., Zhang, Y. (eds) Testbeds and Research Infrastructure: Development of Networks and Communities. TridentCom 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 137. Springer, Cham. https://doi.org/10.1007/978-3-319-13326-3_31

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  • DOI: https://doi.org/10.1007/978-3-319-13326-3_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13325-6

  • Online ISBN: 978-3-319-13326-3

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