Analysis of a Single Server Retrial Queue with Server Vacation and Two Waiting Buffers Based on ATM Networks

This paper presents a discrete-time Geo/G/1 retrial queue with two waiting buffers to model an ATM network, in which the server begins a single vacation in cases where the system is empty at the instant of a service completion. New arriving customer who finds the server being on vacation can decide...

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Main Authors: Shan Gao, Xianchao Wang
Format: Article
Language:English
Published: Hindawi Limited 2019-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2019/4193404
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spelling doaj-bc4f9c8cda6441b0bef47a61f115ccfb2020-11-25T01:18:09ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472019-01-01201910.1155/2019/41934044193404Analysis of a Single Server Retrial Queue with Server Vacation and Two Waiting Buffers Based on ATM NetworksShan Gao0Xianchao Wang1School of Mathematics and Statistics, Fuyang Normal University, Fuyang 236037, ChinaSchool of Computer and Information Engineering, Fuyang Normal University, Fuyang 236037, ChinaThis paper presents a discrete-time Geo/G/1 retrial queue with two waiting buffers to model an ATM network, in which the server begins a single vacation in cases where the system is empty at the instant of a service completion. New arriving customer who finds the server being on vacation can decide to either enter the retrial buffer with some probability p or leave the system with complementary probability 1−p. But the new arriving customer can begin its service immediately if he finds the server idle and join the original buffer if he finds the server busy. We first carry out an extensive analysis of the model by using the supplementary variable method and the generating function approach, and give some performance measures, such as server’s state probabilities and mean queue lengths in the original buffer, retrial buffer, and in the system. Secondly, we give the generating function of the sojourn time of a customer in the system and prove that Little’s law still holds in our model. Sensitivity analysis and cost optimization are finally given for illustrative purposes.http://dx.doi.org/10.1155/2019/4193404
collection DOAJ
language English
format Article
sources DOAJ
author Shan Gao
Xianchao Wang
spellingShingle Shan Gao
Xianchao Wang
Analysis of a Single Server Retrial Queue with Server Vacation and Two Waiting Buffers Based on ATM Networks
Mathematical Problems in Engineering
author_facet Shan Gao
Xianchao Wang
author_sort Shan Gao
title Analysis of a Single Server Retrial Queue with Server Vacation and Two Waiting Buffers Based on ATM Networks
title_short Analysis of a Single Server Retrial Queue with Server Vacation and Two Waiting Buffers Based on ATM Networks
title_full Analysis of a Single Server Retrial Queue with Server Vacation and Two Waiting Buffers Based on ATM Networks
title_fullStr Analysis of a Single Server Retrial Queue with Server Vacation and Two Waiting Buffers Based on ATM Networks
title_full_unstemmed Analysis of a Single Server Retrial Queue with Server Vacation and Two Waiting Buffers Based on ATM Networks
title_sort analysis of a single server retrial queue with server vacation and two waiting buffers based on atm networks
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2019-01-01
description This paper presents a discrete-time Geo/G/1 retrial queue with two waiting buffers to model an ATM network, in which the server begins a single vacation in cases where the system is empty at the instant of a service completion. New arriving customer who finds the server being on vacation can decide to either enter the retrial buffer with some probability p or leave the system with complementary probability 1−p. But the new arriving customer can begin its service immediately if he finds the server idle and join the original buffer if he finds the server busy. We first carry out an extensive analysis of the model by using the supplementary variable method and the generating function approach, and give some performance measures, such as server’s state probabilities and mean queue lengths in the original buffer, retrial buffer, and in the system. Secondly, we give the generating function of the sojourn time of a customer in the system and prove that Little’s law still holds in our model. Sensitivity analysis and cost optimization are finally given for illustrative purposes.
url http://dx.doi.org/10.1155/2019/4193404
work_keys_str_mv AT shangao analysisofasingleserverretrialqueuewithservervacationandtwowaitingbuffersbasedonatmnetworks
AT xianchaowang analysisofasingleserverretrialqueuewithservervacationandtwowaitingbuffersbasedonatmnetworks
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