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Fundamentals of Queueing Networks

90,94 €*

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Produktnummer: 184f830179638e41ea8c2443027781bde4
Autor: Chen, Hong Yao, David D.
Themengebiete: Jackson network Kelly network Queuing Queuing Networks communication operations research optimization scheduling statistics stochastic network
Veröffentlichungsdatum: 15.06.2001
EAN: 9780387951669
Sprache: Englisch
Seitenzahl: 406
Produktart: Gebunden
Verlag: Springer US
Untertitel: Performance, Asymptotics, and Optimization
Produktinformationen "Fundamentals of Queueing Networks"
The objective of this book is to collect in a single volume the essentials of stochastic networks, from the classical product-form theory to the more re cent developments such as diffusion and fluid limits, stochastic comparisons, stability, control (dynamic scheduling) and optimization. The selection of materials inevitably is a reflection upon our bias and preference, but it is also driven to a large extent by our desire to provide a graduate-level text that is well balanced in breadth and depth, suitable for the classroom. Given the wide-ranging applications of stochastic networks in recent years, from supply chains to telecommunications, it is also our hope that the book will serve as a useful reference for researchers and students alike in these diverse fields. The book consists of three parts. The first part, Chapters 1 through 4, covers (continuous-time) Markov-chain models, including the classical Jackson and Kelly networks, the notion of quasi-reversible queues, and stochastic comparisons. The second part, Chapters 5 through 10, focuses on Brownian models, including limit theorems for generalized Jackson net works and multiclass feedforward networks, an in-depth examination of stability in a Kumar-Seidman network, and Brownian approximations for general multiclass networks with a mixture of priority and first-in-first-out disciplines. The third part, Chapters 11 and 12, discusses scheduling in both queueing (stochastic) and fluid (deterministic) networks, along with topics such as conservation laws, polymatroid optimization, and linear pro gramming.

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