The accuracy of Markov chain models in predicting packet-loss statistics for a single multiplexer

Xunqi Yu, James W. Modestino, Xusheng Tian

Research output: Contribution to journalArticle

9 Scopus citations

Abstract

In this correspondence, we investigate the accuracy of low-complexity discrete-time Markov chain models in characterizing the packet-loss process associated with a transport network whose behavior can be described in terms of a single bottleneck node, modeled by a single multiplexer. The results are useful since network behavior is often characterized in terms of a single bottleneck node and it is of some interest to establish the accuracy of Markov chain models in predicting the packet-loss process on even such a simplified network model. We demonstrate that, although higher order Markov chain models can achieve increasingly more accurate descriptions, the Gilbert model has some serious deficiencies in predicting the packet-loss statistics of the single-multiplexer model for a variety of packet arrival processes. We show that this has some serious consequences for the performance evaluation of forward error correction (FEC) coding schemes using Markov chain models compared to that predicted by an exact queueing analysis of the single-multiplexer model.

Original languageEnglish (US)
Pages (from-to)489-501
Number of pages13
JournalIEEE Transactions on Information Theory
Volume54
Issue number1
DOIs
StatePublished - Jan 1 2008

Keywords

  • Forward error correction (FEC) coding
  • Gilbert model
  • Markov chain models
  • Packet recovery
  • Single-multiplexer model

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Information Systems

Fingerprint Dive into the research topics of 'The accuracy of Markov chain models in predicting packet-loss statistics for a single multiplexer'. Together they form a unique fingerprint.

  • Cite this