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UID:www.tcs.tifr.res.in/event/345
DTSTAMP:20230914T125920Z
SUMMARY:Regenerations in Multiclass Open Queueing Networks
DESCRIPTION:Speaker: Sarat Babu  Moka\n\nAbstract: \nMulticlass open queuei
 ng networks find wide applications in communication\, computer and fabrica
 tion networks. Often one is interested in steady state performance measure
 s associated with these systems. One can use the regenerative structure of
  the process to estimate the steady state performance measures via regener
 ative simulation. In a queueing network\, if all the interarrival times ar
 e Markovian (have exponential distributions)\, it is easy to identify rege
 neration instants\, e.g.\, an instant corresponding to an arrival to an em
 pty network. In this presentation\, we consider networks where interarriva
 l times are generally distributed but have exponential or fatter tails. We
  show that such distributions can be decomposed into mixture of sums of in
 dependent random variables such that at least one of the components is exp
 onentially distributed. This allows an embedded regenerative structure in 
 the Markov process. We show that under mild conditions on the network prim
 itives\, the regenerative mean and standard deviation estimators are consi
 stent and satisfy a joint central limit theorem. This is important as it a
 llows construction of asymptotically valid confidence intervals. We show t
 hat amongst all such interarrival time decompositions\, the one with large
 st mean exponential component minimizes the asymptotic variance of the sta
 ndard deviation estimator.\n
URL:https://www.tcs.tifr.res.in/web/events/345
DTSTART;TZID=Asia/Kolkata:20130305T113000
DTEND;TZID=Asia/Kolkata:20130305T130000
LOCATION:A-212 (STCS Seminar Room)
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