Modeling and Performance Evaluation of Computer Communication Networks

Introduction to modeling of computer communication networks using stochastic processes: brief review of discrete random variables, Bernoulli processes and sums of independent random variables, Poisson processes and their main properties, discrete time Markov Chains (properties, classification of states, limiting behavior). Introduction to modeling of computer communication networks using Queueing Theory (Little’s Theorem, the M/M/1, M/M/m, M/M/m/m markovian queues, the M/G/1 queue with generalized service times distribution, the M/G/1 queue with vacations of the server, priority queues). Design, modeling and performance evaluation of multiple access protocols and transmission scheduling schemes for packet radio networks and wireless integrated services networks.

Objectives

The student upon successful completion of the course is expected to understand and can handle stochastic processes and queuing models, which are necessary for modeling and studying performance communications networks.

Prerequisites

Basic knowledge of probabilty theory and calculus

Syllabus

Introduction to modeling of computer communication networks using stochastic processes: brief review of discrete random variables, Bernoulli processes and sums of independent random variables, Poisson processes and their main properties, discrete time Markov Chains (properties, classification of states, limiting behavior). Introduction to modeling of computer communication networks using Queueing Theory (Little’s Theorem, the M/M/1, M/M/m, M/M/m/m markovian queues, the M/G/1 queue with generalized service times distribution, the M/G/1 queue with vacations of the server, priority queues). Design, modeling and performance evaluation of multiple access protocols and transmission scheduling schemes for packet radio networks and wireless integrated services networks.