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Automatic metadata generation for active measurement

Published:01 November 2017Publication History

ABSTRACT

Empirical research in the Internet is fraught with challenges. Among these is the possibility that local environmental conditions (e.g., CPU load or network load) introduce unexpected bias or artifacts in measurements that lead to erroneous conclusions. In this paper, we describe a framework for local environment monitoring that is designed to be used during Internet measurement experiments. The goals of our work are to provide a critical, expanded perspective on measurement results and to improve the opportunity for reproducibility of results. We instantiate our framework in a tool we call SoMeta, which monitors the local environment during active probe-based measurement experiments. We evaluate the runtime costs of SoMeta and conduct a series of experiments in which we intentionally perturb different aspects of the local environment during active probe-based measurements. Our experiments show how simple local monitoring can readily expose conditions that bias active probe-based measurement results. We conclude with a discussion of how our framework can be expanded to provide metadata for a broad range of Internet measurement experiments.

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      • Published in

        cover image ACM Conferences
        IMC '17: Proceedings of the 2017 Internet Measurement Conference
        November 2017
        509 pages
        ISBN:9781450351188
        DOI:10.1145/3131365

        Copyright © 2017 ACM

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        • Published: 1 November 2017

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