Martingale proofs of many-server heavy-traffic limits for Markovian queues

Guodong Pang, Rishi Talreja, Ward Whitt

Research output: Contribution to journalArticlepeer-review

130 Scopus citations

Abstract

This is an expository review paper illustrating the "martingale method" for proving many-server heavy-traffic stochastic-process lim- its for queueingmodels, supporting diffusion-process approximations.Care- ful treatment is given to an elementary model - the classical infinite-server model M/M/∞, but models with finitely many servers and customer aban- donment are also treated. The Markovian stochastic process representing the number of customers in the system is constructed in terms of rate- 1 Poisson processes in two ways: (i) through random time changes and (ii) through random thinnings. Associated martingale representations are obtained for these constructions by applying, respectively: (i) optional stop- ping theorems where the random time changes are the stopping times and (ii) the integration theorem associated with random thinning of a counting process. Convergence to the diffusion process limit for the appropriate sequence of scaled queueing processes is obtained by applying the continuous mapping theorem. A key FCLT and a key FWLLN in this framework are established both with and without applying martingales.

Original languageEnglish (US)
Pages (from-to)193-267
Number of pages75
JournalProbability Surveys
Volume4
Issue number1
DOIs
StatePublished - 2007

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

Fingerprint

Dive into the research topics of 'Martingale proofs of many-server heavy-traffic limits for Markovian queues'. Together they form a unique fingerprint.

Cite this