On the Impact of Clustering on Measurement Reduction

(Work in Progress)
  • Damien Saucez
  • Benoit Donnet
  • Olivier Bonaventure
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5550)


Measuring a path performance according to one or several metrics, such as delay or bandwidth, is becoming more and more popular for applications. However, constantly probing the network is not suitable. To make measurements more scalable, the notion of clustering has emerged. In this paper, we demonstrate that clustering can limit the measurement overhead in such a context without loosing too much accuracy. We first explain that measurement reduction can be observed when vantage points collaborate and use clustering to estimate path performance. We then show, with real traces, how effective is the overhead reduction and what is the impact in term of measurement accuracy.


clustering BGP reduction measurement 


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Copyright information

© IFIP International Federation for Information Processing 2009

Authors and Affiliations

  • Damien Saucez
    • 1
  • Benoit Donnet
    • 1
  • Olivier Bonaventure
    • 1
  1. 1.CSE DeparmentUniversitè catholique de LouvainBelgium

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