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SIGMETRICS
2002
ACM

Maximum likelihood network topology identification from edge-based unicast measurements

9 years 3 months ago
Maximum likelihood network topology identification from edge-based unicast measurements
Network tomography is a process for inferring "internal" link-level delay and loss performance information based on end-to-end (edge) network measurements. These methods require knowledge of the network topology; therefore a first crucial step in the tomography process is topology identification. This paper considers the problem of discovering network topology solely from host-based, unicast measurements, without internal network cooperation. First, we introduce a novel delay-based measurement scheme that does not require clock synchronization, making it more practical than other previous proposals. Due to the nature of the measurement procedure, our methodology has the potential to identify layer two switching elements (provided they are logical topology branching points and induce some measurable switching delay). Second, we propose a maximum penalized likelihood criterion for topology identification. This is a global optimality criterion, in contrast to other recent propo...
Mark Coates, Rui Castro, Robert Nowak, Manik Gadhi
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 2002
Where SIGMETRICS
Authors Mark Coates, Rui Castro, Robert Nowak, Manik Gadhiok, Ryan King, Yolanda Tsang
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