Paper Info
Title
Joint end-to-end loss-delay hidden Markov model for periodic UDP traffic over the Internet
Abstract
Performance of real-time applications on network communication channels is strongly related to losses and temporal delays. Several studies showed that these network features may be correlated and exhibit a certain degree of memory such as bursty losses and delays. The memory and the statistical dependence between losses and temporal delays suggest that the channel may be well modeled by a hidden Markov model (HMM) with appropriate hidden variables that capture the current state of the network. In this paper, an HMM is proposed that shows excellent performance in modeling typical channel behaviors in a set of real packet links. The system is trained with a modified version of the Expectation-Maximization (EM) algorithm. Hidden-state analysis shows how the state variables characterize channel dynamics. State-sequence estimation is obtained by the use of Viterbi algorithm. Real-time modeling of the channel is the first step to implement adaptive communication strategies.
Year
DOI
Venue
2006
10.1109/TSP.2005.861066
IEEE Transactions on Signal Processing
Keywords
Field
DocType
hidden markov models,expectation maximization,viterbi algorithm,internet,maximum likelihood estimation,communication channels,real time,transport protocols,em algorithm,hidden markov model,hidden variables,network model
Forward algorithm,Control theory,Computer science,Network packet,Communication channel,Algorithm,Speech recognition,Bayesian network,Hidden Markov model,Viterbi algorithm,Network model,Hidden semi-Markov model
Journal
Volume
Issue
ISSN
54
2
1053-587X
Citations 
PageRank 
References 
14
0.93
9
Authors
4
Name
Order
Citations
PageRank
Pierluigi Salvo Rossi132827.27
Gianmarco Romano220516.19
Francesco Palmieri31713182.92
G. Iannello49713.87