Analysis and optimization of vacation and polling models with retrials

M.A. Abidini; O.J. Boxma; J.A.C. Resing

doi:10.1016/j.peva.2016.02.001

Analysis and optimization of vacation and polling models with retrials

M.A. Abidini, O.J. Boxma, J.A.C. Resing

Stochastic Operations Research

Research output: Contribution to journal › Article › Academic › peer-review

14 Citations (Scopus)

33 Downloads (Pure)

Abstract

We study a vacation-type queueing model, and a single-server multi-queue polling model, with the special feature of retrials. Just before the server arrives at a station there is some deterministic glue period. Customers (both new arrivals and retrials) arriving at the station during this glue period will be served during the visit of the server. Customers arriving in any other period leave immediately and will retry after an exponentially distributed time. Our main focus is on queue length analysis, both at embedded time points (beginnings of glue periods, visit periods and switch- or vacation periods) and at arbitrary time points.

Original language	English
Pages (from-to)	52-69
Number of pages	18
Journal	Performance Evaluation
Volume	98
DOIs	https://doi.org/10.1016/j.peva.2016.02.001
Publication status	Published - 1 Apr 2016

Keywords

Polling model
Retrials
Vacation queue

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10.1016/j.peva.2016.02.001

abidanal2016Final published version, 1.03 MBLicence: TAVERNE

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AB - We study a vacation-type queueing model, and a single-server multi-queue polling model, with the special feature of retrials. Just before the server arrives at a station there is some deterministic glue period. Customers (both new arrivals and retrials) arriving at the station during this glue period will be served during the visit of the server. Customers arriving in any other period leave immediately and will retry after an exponentially distributed time. Our main focus is on queue length analysis, both at embedded time points (beginnings of glue periods, visit periods and switch- or vacation periods) and at arbitrary time points.

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KW - Vacation queue

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JO - Performance Evaluation

JF - Performance Evaluation

ER -

Analysis and optimization of vacation and polling models with retrials

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Keywords

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