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Multiple source network tomography: a hypothesis-testing approach

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3 Author(s)
Rabbat, M. ; Wisconsin Univ., Madison, WI, USA ; Nowak, R. ; Coates, M.

Summary form only given. Knowledge of internal network behaviour is of fundamental importance for a variety of problems such as routing optimization and anomaly detection. The problem of inferring network characteristics using end-to-end measurements is referred to as network tomography. This paper investigates the multiple-source, multiple-receiver (M-by-N) network tomography problem. We identify the dichotomy of 2-by-2 topology components and show that their consideration is sufficient for solving the general M-by-N problem. We describe a probing methodology and decompose the tomography problem into two stages: a series of generalized likelihood ratio tests that determine the appropriate data aggregation, followed by maximum likelihood estimation.

Published in:

Statistical Signal Processing, 2003 IEEE Workshop on

Date of Conference:

28 Sept.-1 Oct. 2003