Introduction to Queueing Theory and Stochastic Teletraffic Models

TL;DR

This book-grounded text builds a solid probability and stochastic-process foundation for queueing theory and teletraffic. It emphasizes steady-state analyses, simulation-based learning, and a progression from basic probability to complex teletraffic models including deterministic, Markovian, and networked queues. The work connects theory to telecommunications applications through link-dimensioning, insensitivity properties, and scalable approximations. By combining rigorous derivations with guided computational exercises, it aims to equip readers to model, simulate, and dimension real-world telecommunication systems.

Abstract

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 modelling, resource provisioning and traffic management. These study areas are often collectively called teletraffic. This book assumes prior knowledge of a programming language, mathematics, probability and stochastic processes normally taught in an electrical engineering course. For students who have some but not sufficiently strong background in probability and stochastic processes, we provide, in the first few chapters, background on the relevant concepts in these areas.