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Implementation and Deployment of a Distributed Network Topology Discovery Algorithm

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Abstract for the technical report "Implementation and Deployment of a Distributed Network Topology Discovery Algorithm" authored by Benoit Donnet, Bradley Huffaker, Timur Friedman, and kc claffy.
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Implementation and Deployment of a Distributed Network Topology Discovery Algorithm: Technical Report

Benoit Donnet
Université Pierre & Marie Curie
Laboratoire LiP6/CNRS, UMR 7606, France
and
Cooperative Association for Internet Data Analysis - CAIDA
San Diego Supercomputer Center,
University of California, San Diego

Bradley Huffaker, kc claffy
Cooperative Association for Internet Data Analysis - CAIDA
San Diego Supercomputer Center,
University of California, San Diego

Timur Friedman
Université Pierre & Marie Curie
Laboratoire LiP6/CNRS, UMR 7606, France

Abstract: In the past few years, the network measurement community has been interested in the problem of internet topology discovery using a large number (hundreds or thousands) of measurement monitors. The standard way to obtain information about the internet topology is to use the traceroute tool from a small number of monitors. Recent papers have made the case that increasing the number of monitors will give a more accurate view of the topology. However, scaling up the number of monitors is not a trivial process. Duplication of effort close to the monitors wastes time by reexploring well-known parts of the network, and close to destinations might appear to be a distributed denialof service (DDoS) attack as the probes converge from a set of sources towards a given destination. In prior work, authors of this report proposed Doubletree, an algorithm for cooperative topology discovery, that reduces the load on the network, i.e., router IP interfaces and end-hosts, while discovering almost as many nodes and links as standard approaches based on traceroute. This report presents our open-source and freely downloadable implementation of Doubletree in a tool we call traceroute@home. We describe the deployment and validation of traceroute@home on the PlanetLab testbed and we report on the lessons learned from this experience. We discuss how traceroute@home can be developed further and discuss ideas for future improvements.

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