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BBL 541E - Modeling & Analysis of Markovian Systems

Course Objectives

1) To give the basics of Markov modeling through Memoryless and Markov properties
2) To teach modeling and analysis using Markov chains
3) To analyze various Markovian queueing systems and their generalizations
4) To show real life examples from the IT world that Markovian analysis is applicable

Course Description

Review of probability theory and random processes, memoryless property, Markov property, renewal processes, Poisson process, discrete- and continuous-time Markov chains, classification, properties, Chapman–Kolmogorov equations, steady-state solutions, birth-death processes, balance equations, Little's Law, M/M/1, M/M/k, M/M/k/k and M/M/k/k/N systems, Erlang formulas, Markovian arrival process (MAP) arrivals, phase-type service times, Aloha systems, other special topics

Course Coordinator
Mehmet Akif Yazıcı
Course Language
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