Efficient and reliable network tomography in heterogeneous networks using BitTorrent broadcasts and clustering algorithms

TL;DR

This paper introduces a fast, reliable network tomography method that uses BitTorrent broadcast fragment counts and clustering algorithms to reconstruct network topology and bandwidth bottlenecks efficiently.

Contribution

It presents a novel, efficient approach combining BitTorrent-based measurements with clustering algorithms for network tomography in heterogeneous networks.

Findings

Successfully reconstructs network clusters and bottlenecks

Efficiently estimates link bandwidths in complex networks

Reduces measurement time compared to traditional methods

Abstract

In the area of network performance and discovery, network tomography focuses on reconstructing network properties using only end-to-end measurements at the application layer. One challenging problem in network tomography is reconstructing available bandwidth along all links during multiple source/multiple destination transmissions. The traditional measurement procedures used for bandwidth tomography are extremely time consuming. We propose a novel solution to this problem. Our method counts the fragments exchanged during a BitTorrent broadcast. While this measurement has a high level of randomness, it can be obtained very efficiently, and aggregated into a reliable metric. This data is then analyzed with state-of-the-art algorithms, which reliably reconstruct logical clusters of nodes inter-connected by high bandwidth, as well as bottlenecks between these logical clusters. Our experiments demonstrate that the proposed two-phase approach efficiently solves the presented problem for a number of settings on a complex grid infrastructure.