Title :
Estimate Link-Level Transition Matrix from End-to-End Observations
Author_Institution :
Univ. of New South Wales at ADFA, Canberra, ACT, Australia
Abstract :
Network tomography aims to estimate network characteristics from end-to-end (e2e) observation, e.g. link-level loss rate and delay distribution. In this paper, a method is proposed to estimate link-level transition matrix from e2e observations. The estimate obtained from the proposed method is an MLE. Simulation study shows the estimate obtained by the proposed method is very close to the direct measurement that makes it possible to use the estimated characteristic to predict the performance of a link or a path for a short period.
Keywords :
hidden Markov models; information networks; maximum likelihood estimation; HMM; end-to-end observations; hidden Markov model; link-level transition matrix estimation; network characteristics; network tomography; Australia; Bandwidth; Delay estimation; Hidden Markov models; Markov processes; Maximum likelihood estimation; Predictive models; State estimation; Telecommunication traffic; Tomography; Network tomography; temporal tomography; transition matrix;
Conference_Titel :
Information Engineering, 2009. ICIE '09. WASE International Conference on
Conference_Location :
Taiyuan, Shanxi
Print_ISBN :
978-0-7695-3679-8
DOI :
10.1109/ICIE.2009.85
