Stochastic Modeling and the Theory of Queues

Overview

This is a PG level course on discrete stochastic processes and queuing, aimed at students working in areas such as communication networks, operations research, and machine learning. It covers Poisson processes, renewal processes, renewal reward theory, queuing models and analyses, Markov chains in discrete as well as continuous time (countable state-space only). A graduate level probability background will be assumed.INTENDED AUDIENCE : This is a PG/PhD level course on discrete stochastic processes, which will also cover queuing examples and applications.PREREQUISITES : EE5110: Probability Foundations for EEhttps://nptel.ac.in/courses/108/106/108106083/INDUSTRIES SUPPORT : NIL

Syllabus

Week-1:Poisson Processes
Week-2:Poisson Processes
Week-3:Renewal Processes and Renewal Reward Theory Week-4:Renewal Processes and Renewal Reward Theory
Week-5:Renewal Processes and Renewal Reward Theory
Week-6:Renewal Processes and Renewal Reward Theory
Week-7:Discrete Time Markov Chains (DTMCs)
Week-8:Discrete Time Markov Chains (DTMCs)
Week-9:Discrete Time Markov Chains (DTMCs)
Week-10:Continuous Time Markov Chains
Week-11:Continuous Time Markov Chains
Week-12:Continuous Time Markov Chains