z-logo
open-access-imgOpen Access
Efficient and Reliable Network Tomography in Heterogeneous Networks Using Bittorrent Broadcasts and Clustering Algorithms
Author(s) -
Kiril Dichev,
Fergal Reid,
Alexey Lastovetsky
Publication year - 2013
Publication title -
scientific programming
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.269
H-Index - 36
eISSN - 1875-919X
pISSN - 1058-9244
DOI - 10.1155/2013/746524
Subject(s) - computer science , network tomography , bandwidth (computing) , cluster analysis , algorithm , bittorrent , randomness , distributed computing , grid , computer network , theoretical computer science , data mining , network topology , artificial intelligence , peer to peer , mathematics , statistics , geometry
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 correctly reconstruct logical clusters of nodes interconnected 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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom