Vladimir Anisimov & Nikolaos Limnios 
Queueing Theory 1 [EPUB ebook] 
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The aim of this book is to reflect the current cutting-edge thinking and established practices in the investigation of queueing systems and networks.
This first volume includes ten chapters written by experts well-known in their areas. The book studies the analysis of queues with interdependent arrival and service times, characteristics of fluid queues, modifications of retrial queueing systems and finite-source retrial queues with random breakdowns, repairs and customers’ collisions. Some recent tendencies in the asymptotic analysis include the average and diffusion approximation of Markov queueing systems and networks, the diffusion and Gaussian limits of multi-channel queueing networks with rather general input flow, and the analysis of two-time-scale nonhomogenous Markov chains using the large deviations principle.
The book also analyzes transient behavior of infinite-server queueing models with a mixed arrival process, the strong stability of queueing systems and networks, and applications of fast simulation methods for solving high-dimension combinatorial problems.

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A propos de l’auteur

Vladimir Anisimov is Full Professor in Applied Statistics. He works in the
Center for Design & Analysis at Amgen Inc. in London, UK. His research
interests include probability models and stochastic processes, clinical
trials modeling, applied statistics, queueing models and asymptotic
techniques.
Nikolaos Limnios is Full Professor in Applied Mathematics at the
University of Technology of Compiegne, part of the Sorbonne University
Group, in France. His research interests include stochastic processes
and statistics, Markov and semi-Markov processes, random evolutions
with applications in reliability, queueing systems, earthquakes and
biology.

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Langue Anglais ● Format EPUB ● Pages 336 ● ISBN 9781119755425 ● Taille du fichier 8.9 MB ● Éditeur Vladimir Anisimov & Nikolaos Limnios ● Maison d’édition John Wiley & Sons ● Publié 2021 ● Édition 1 ● Téléchargeable 24 mois ● Devise EUR ● ID 7828336 ● Protection contre la copie Adobe DRM
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