Introduction to queueing theory and stochastic teletraffic models$^1$.
The aim of this textbook is to provide students with basic knowledge of stochastic models
that may apply to telecommunications research areas, such as traffic modeling, performance
evaluation, resource provisioning, and traffic management. These research areas are included in a field called teletraffic.
Introduction to queueing theory$^2$.
This book is one of the best introductory books in the field, the good thing about this book is, the video lectures of Prof. Cooper can be found on the net and you can easily follow the book base on the lectures.
An introduction to queueing theory: modeling and analysis in applications$^3$.
With an emphasis on modeling and analysis this book deals with topics such as identification of models, collection of data, and tests for stationarity and independence of observations. It provides a rigorous treatment of basic models commonly used in applications with references for advanced topics. It gives a comprehensive discussion of statistical inference techniques usable in the modeling of queueing systems and an introduction to decision problems in their management. The book also includes a chapter, written by computer scientists, on the use of computational tools and simulation in solving queueing theory problems.
Markov Chains: Models, Algorithms and Applications$^4$.
The mentioned two chapters are very good examples of modeling: Chapter 2 discusses the applications of continuous-time Markov chains to model queueing systems and discrete-time Markov chain for computing the PageRank, the ranking of websites on the Internet. Chapter 3 studies Markovian models for manufacturing and re-manufacturing systems and presents closed-form solutions and fast numerical algorithms for solving the captured systems.
Queues A Course in Queueing Theory$^5$.
The first three chapters focus on the needed preliminaries, including exposition distributions, Poisson processes and generating functions, renewal theory, and Markov chains, Then, rather than switching to first-come-first-served memoryless queues here as most texts do, Haviv discusses the M/G/1 model instead of the M/M/1, and then covers priority queues. Later chapters cover the G/M/1 model, thirteen examples of continuous-time Markov processes, open networks of memoryless queues and closed networks, queueing regimes with insensitive parameters, and then concludes with two-dimensional queueing models which are quasi birth and death processes. Each chapter ends with exercises.
1) Zukerman, Moshe. "Introduction to queueing theory and stochastic teletraffic models." arXiv preprint arXiv:1307.2968 (2013).
2) Cooper, Robert B. Introduction to queueing theory. North Holland, 1981.
3) Bhat, U. Narayan. An introduction to queueing theory: modeling and analysis in applications. Birkhäuser, 2015.
4) Ching, Wai-Ki, and Michael K. Ng. "Markov chains." Models, algorithms and applications (2006).
5) Haviv, Moshe. Queues: A Course in Queueing Theory. Vol. 191. Springer Science & Business Media, 2013.