Issues with inferring Internet topological attributes

  • Authors:
  • Lisa Amini;Anees Shaikh;Henning Schulzrinne

  • Affiliations:
  • IBM Research, 19 Skyline Drive, Hawthorne, NY 10532, USA and Department of Computer Science, Columbia University, 450 Computer Science Building, 1213 Amsterdam Avenue, New York, NY 10027-7003, USA;IBM Research, 19 Skyline Drive, Hawthorne, NY 10532, USA;Department of Computer Science, Columbia University, 450 Computer Science Building, 1213 Amsterdam Avenue, New York, NY 10027-7003, USA

  • Venue:
  • Computer Communications
  • Year:
  • 2004

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Abstract

A number of recent studies of Internet network structure are based on data collected from inter-domain BGP routing tables and tools, such as traceroute, to probe end-to-end paths. The goal of these studies is often to infer Internet topological properties. There is growing evidence, however, that the amount and diversity of the data has a significant impact on the conclusions drawn about some of the structural properties. While systematic data collection from a number of network vantage points can reduce certain ambiguities, thus far, no methods have been reported for fully resolving these issues. The goal of our study was to quantify the effects of these anomalies on key Internet structural attributes. We report on our analysis of over 290,000 measurements from globally distributed sites. We contrast results obtained from router-level measurements with those obtained from BGP routing tables, and offer insights as to why certain inferred properties differ. We use multiple views of the same data to demonstrate that some topological attributes, such as the average path length, are relatively consistent across a variety of data sources. We also illustrate how using the same methodology to model other attributes, such as those based on the actual forwarding path between a pair of nodes, or the level of AS path asymmetry, can produce substantially misleading results.