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Ayyappan, G.; Shyamala, S.

doi:10.1155/2014/892867

Cited by 3 publications

(1 citation statement)

References 18 publications

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“…Balasubramanian et al (2010) analysed the steady state behaviour of a non-Markovian queueing system with overloading and multiple vacations." " Ayyappan and Shyamala (2014) have discussed a non-Markovian batch arrival queue with setup time, Bernoulli vacation, breakdown and delayed repair." Transient and steady state solutions of queue size have been derived explicitly. "…”

Section: Introductionmentioning

confidence: 99%

An M[X]/G(a, b)/1 queue with unreliable server, second optional service, closedown, setup with N-policy and multiple vacation

Ayyappan

Nirmala

2020

IJMOR

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Batch arrival bulk service queueing system has been effectively used to model many real life systems like production, manufacturing, transportation as well as telecommunication. Characteristic like second optional service, service interruption, closedown time, multiple vacation, setup time with N policy, etc. have been respectively considered in such models. So far, no comprehensive combination of these characteristics have been reported in the literature. This paper deals with the analysis of a non-Markovian batch arrival bulk service queue with a general combination of all the above mentioned characteristics.

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Section: Introductionmentioning

confidence: 99%

An M[X]/G(a, b)/1 queue with unreliable server, second optional service, closedown, setup with N-policy and multiple vacation

Ayyappan

Nirmala

2020

IJMOR

Self Cite

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Random Policy for an Unreliable Server System With Delaying Repair and Setup Time Under Bernoulli Vacation Schedule

Huang

Wang

2016

Journal of Testing and Evaluation

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This paper deals with an M/G/1 queuing system with server setup and a Bernoulli vacation schedule, in which an unreliable server applies a random N-policy. The server may break down at any time, and the service channel will fail for the duration of the breakdown. When units in the queue are exhaustively served, the server will become idle until the queue size grows to meet a random threshold N(≥1). As soon as the queue size reaches N, the server will immediately begin to serve the waiting units. Upon the service completion of each unit, the server may take a vacation or may remain in the system to serve the next unit, if any. This study derives the queue size distribution during a busy period initiation epoch and a departure epoch, respectively. We also give the analytic expression for the distribution of the delay busy period, which includes breakdown periods and actual busy periods. Furthermore, numerical examples of the long-run cost functions for the random N-policy and the classical N-policy are investigated.

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Queuing Strategy in Deep-Ocean Assessment and Reporting of Tsunamis (DART)

Radha

Maragathasundari

Manikandan

2021

Journal of Testing and Evaluation

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This paper investigates an examination on a lining system in Deep-ocean Assessment and Reporting of Tsunamis (DART). DART is an element of an improved tsunami warning system. By changing the order in solar high temperature and thickness and diffusing the information through an outward float to a station on the ground by satellite, DART empowers moment and precise tidal wave gauges. Here we study a Queuing issue that occurs during the hour of DART. The Queuing issue is changed into a scientific Queuing model, and it is settled by methods for a supplementary variable procedure of a lining process. We infer the likelihood of creating a function of the queue size and the exhibition proportions of the framework viz. mean length of the queue size and normal waiting time of the line. Likewise, we figure the inactive time and usage factor of the base weight recorder (Server). The model is very much clarified by the methods for diagrammatic portrayal. The model is all-around clarified in detail by the methods for its application. In addition, it is all-around legitimized by the methods for numerical representation and graphical methodology.

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MX/G1, G2/1

Cited by 3 publications

References 18 publications

An <i>M</i><SUP align="right">[<i>X</i>]</SUP>/<i>G</i>(<i>a</i>, <i>b</i>)/1 queue with unreliable server, second optional service, closedown, setup with N-policy and multiple vacation

An <i>M</i><SUP align="right">[<i>X</i>]</SUP>/<i>G</i>(<i>a</i>, <i>b</i>)/1 queue with unreliable server, second optional service, closedown, setup with N-policy and multiple vacation

Random Policy for an Unreliable Server System With Delaying Repair and Setup Time Under Bernoulli Vacation Schedule

Queuing Strategy in Deep-Ocean Assessment and Reporting of Tsunamis (DART)

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