Work

Finding the Right Tree: Topology Inference Despite Spatial Dependences

Year: 2017

Type: article

Abstract: Network tomographic techniques have almost exclusively been built on a strong assumption of mutual independence of link processes. We introduce model classes for link loss processes with non-trivial spatial dependencies, for which the tree topology is nonetheless identifiable from leaf measurements using multicast probing. We show that these classes are large in a well-defined sense, and we provide an algorithm, SLTD, capable of returning the correct topology with certainty in the limit of infinite data.

Source: IEEE Transactions on Information Theory

DOI: 10.1109/tit.2017.2739779

Authors: Rhys Bowden, Darryl Veitch

Institutions: The University of Melbourne, University of Technology Sydney

Language: English

Topic: Network Traffic and Congestion Control

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Australian Research Council

Awards: Overseeing the internet: new paradigms of network measurement, New stochastic models for Science, Economics, Social Science and Engineering