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Tomographic Node Placement Strategies and the Impact of the Routing Model

Published:19 December 2017Publication History
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Abstract

Fault-tolerant computer networks rely on mechanisms supporting the fast detection of link failures. Tomographic techniques can be used to implement such mechanisms at low cost: it is often sufficient to deploy a small number of tomography nodes exchanging probe messages along paths between them and detect link failures based on these messages. Our paper studies a practically relevant aspect of network tomography: the impact of the routing model.

While the relevance of the routing model on path diversity and hence tomography cost is obvious and well-known on an anecdotal level, we lack an analytical framework to quantify the influence of different routing models (such as destination-based routing) exists. This paper fills this gap and introduces a formal model for asymmetric network tomography and a taxonomy of path routing models. This facilitates algorithmic reasoning about tomographic placement problems and quantifying the difference between routing models. In particular, we provide optimal and near-optimal algorithms to deploy a minimal number of asymmetric and symmetric tomography nodes for basic network topologies (modelled as graphs) under different routing model classes. Interestingly, we find that in many cases routing according to a more restrictive routing model gives better results: compared to a more general routing model, computing a good placement is algorithmically more tractable and does not entail high monitoring costs, a desirable trade-off in practice.

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        cover image Proceedings of the ACM on Measurement and Analysis of Computing Systems
        Proceedings of the ACM on Measurement and Analysis of Computing Systems  Volume 1, Issue 2
        December 2017
        480 pages
        EISSN:2476-1249
        DOI:10.1145/3175501
        Issue’s Table of Contents

        Copyright © 2017 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 19 December 2017
        Published in pomacs Volume 1, Issue 2

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