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Computer Network Projects in Statistics at Boston University Eric D. Kolaczyk Department of Mathematics and Statistics Boston University (Supported by ONR, NSF)

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General Focus: Whole-Network Analysis Graph Wavelets(Crovella & Kolaczyk, INFOCOM03) Network distance metrics and the relation of distance to covariance in network tomography. (Joint with D. Chua, M. Crovella, and A. Lakhina.) Multivariate analysis of network flow data. (BU/Sprint/Intel) Modular strategies for global inter-network monitoring. (UMich/UWisc/BU)

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Teaser: Distance & Covariance We propose a path-based measure of distance between edges (i.e., links) on a network graph. We study the relationship between i. Covariance of link measurements ii. Distance between links Finding: Roughly linear decay of covariance as a function of distance, on a log-log scale.

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Analysis of `Rocketfuel Data

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Relevance to SAMSI Workshop Useful distance metrics critical to whole-network analysis (e.g., see Vardi 2003, IEEE-SPL). Evidence suggests some degree of analogy with classical spatial statistics may obtain. Interesting connections to new questions in random graph theory. See poster by D. Chua Tuesday night!

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3. SMALL WORLDS The Watts-Strogatz model. Watts-Strogatz, Nature 1998 Small world: the average shortest path length in a real network is small Six degrees.

3. SMALL WORLDS The Watts-Strogatz model. Watts-Strogatz, Nature 1998 Small world: the average shortest path length in a real network is small Six degrees.

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