Nowak, Robert D.2009-06-042009-06-042001Tsang, Yau-Yau Yolanda. "Loss inference in unicast network tomography based on TCP traffic monitoring." (2001) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/17471">https://hdl.handle.net/1911/17471</a>.https://hdl.handle.net/1911/17471Network tomography is a promising technique for characterizing the internal behavior of large-scale networks based solely on end-to-end measurements. Despite the efficiency of active probing in most network loss tomography methods, these measurements impose an additional burden on the network in terms of bandwidth and network resources. They can therefore cause the estimated performance parameters to differ substantially from losses suffered by existing TCP traffic flows. In this thesis, we propose a promising passive measurement framework based on the sampling of existing TCP flows. We demonstrate its performance using extensive ns-2 simulations. We observe accurate estimates of link losses (with 2% mean absolute error). We also describe the Expectation-Maximization (EM) algorithm in solving the Maximum Likelihood (ML) Estimates in terms of individual link loss rates as an incomplete data problem. Finally, we present a new method for simultaneously visualizing the network connectivity and the network performance parameters.43 p.application/pdfengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.ElectronicsElectrical engineeringLoss inference in unicast network tomography based on TCP traffic monitoringThesisTHESIS E.E. 2001 TSANG