Communication and Computer Networks

This book presents a unified approach to developing accurate discrete-time models of communication and computer networks, using discrete-time queuing theory and approximation techniques to obtain solutions. The first chapter outlines the basic aims and philosophy of the book and introduces discrete-time queues at the simplest possible level. The chapters that follow cover probability theory and discrete-time Markov chains, delve into discrete-time queues and queuing networks, and focus on applications for satellite and local area networks. In addition, the book gives examples of specific modeling techniques, and covers handling statistically different users, finite channel delays, timing delays, and unsolvable traffic equations.

1. Networks, Queues and Performance Modelling. 1.1 Introduction. 1.2 Network tyes. 1.3 Multiple-access protocols. 1.4 Discrete-time queues. 1.5 Performance measures. 2. Probability, Random Variables, and Distributions. 2.1 Probability. 2.2 Random variables. 2.3 Distributions. 2.4 Conditional distributions. 3. Stochastic Process and Markov Chains. 3.1 Poisson process. 3.2 Properties of the Poisson process. 3.3 Markov chains. 3.4 Markov chain models. 3.5 Exercises. 4. Discrete-Time Queues. 4.1 Performance measures and Litte's result. 4.2 Discrete-time queueing conventions. 4.3 Discrete-time M/M/1 queue. 4.4 Discrete-time M/M/1/J queue. 4.5 Discrete-time M?an/M/1 4.6 Discrete-time M?an/M?dm/ infinity queue. 4.7 S-queues. 4.8 Exercises. 5. Discrete-Time Queueing Networks. 5.1 Tandem S-queues. 5.2 Network of S-queues. 5.3 Discrete-time queueing network models for multiple access protocols. 5.4 Equilibrium point analysis. 5.5 Different customer classes. 5.6 Exercises. 6. Satellite Networks. 6.1 Time-division multiple access. 6.2 Slotted Aloha. 6.3 Code division multiple access. 6.4 Buffered slotted Aloha 6.5 Exercises. 7. Local Area Networks. 7.1 Carrier sensing networks. 7.2 Token passing networks. 7.3 Slotted rings. 7.4 Exercises. Appendix. References. Index.