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Retrial Queueing Systems

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Retrial Queueing Systems
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14 324,00 JPY
Typical price1 089,81 PLN
Lowest (90 days)71,50 PLN
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2026-08-08 2026-08-15
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2026-08-0884,99
2026-08-1571,50
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SP SpringerNatureLink Shop INT 14 299,00 JPY 25,00 JPY 14 324,00 JPY Disponible il y a 15 heures View offer
SP Springer Nature Author 14 299,00 JPY 25,00 JPY 14 324,00 JPY Disponible il y a 1 semaine View offer
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SP SpringerNatureLink Shop INT 109,99 USD 25,00 USD 134,99 USD Disponible il y a 19 heures View offer
SP SpringerNatureLink Shop INT 109,99 USD 29,00 USD 138,99 USD Disponible il y a 19 heures View offer
SP SpringerNatureLink Shop INT 118,00 EUR 25,00 EUR 143,00 EUR Disponible il y a 19 heures View offer

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The application of auto-repeat facilities in telephone systems, as well as the use of random access protocols in computer networks, have led to growing interest in retrial queueing models. Since much of the theory of retrial queues is complex from an analytical viewpoint, with this book the authors give a comprehensive and updated text focusing on approximate techniques and algorithmic methods for solving the analytically intractable models. Retrial Queueing Systems: A Computational Approach also Presents motivating examples in telephone and computer networks. Establishes a comparative analysis of the retrial queues versus standard queues with waiting lines and queues with losses. Integrates a wide range of techniques applied to the main M/G/1 and M/M/c retrial queues, and variants with general retrial times, finite population and the discrete-time case. Surveys basic results of the matrix-analytic formalism and emphasizes the related tools employed in retrial queues. Discusses a few selected retrial queues with QBD, GI/M/1 and M/G/1 structures. Features an abundance of numerical examples, and updates the existing literature. The book is intended for an audience ranging from advanced undergraduates to researchers interested not only in queueing theory, but also in applied probability, stochastic models of the operations research, and engineering. The prerequisite is a graduate course in stochastic processes, and a positive attitude to the algorithmic probability.

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