CS 5291 Stochastic Processes for Networking

1. CS 5291Stochastic Processes for Networking Instructor: Shun-Ren YangOffice: EECS 3202Email: sryang@cs.nthu.edu.twOffice Hour: Tuesday morning 10:00-12:00

2. People • Instructor: Shun-Ren Yang • Office: EECS 3202 • Tel: ext. 31212 • Email: sryang@cs.nthu.edu.tw • Office hours: • Tuesday morning 10:00-12:00 • Appointment via Email • TA: • 王昱傑 • Email: s100064525@m100.nthu.edu.tw • Office: 台達館 705 • Phone: ext. 80920 • Office hours: to be determined

3. Course Outline • Preliminaries • Random Variables and Stochastic Processes, • Probability and Expectations, • Probability Inequalities; • Poisson Processes • Introduction, • Properties, • Non-homogeneous Poisson Processes, • Compound Poisson Processes, • Poisson Arrival See Time Average (PASTA); • Renewal Processes • Introduction, • Limit Theorems, • Key Renewal Theorems, • Renewal Reward Processes, • Delayed Renewal Processes, • Regenerative Processes;

4. Course Outline • Discrete-Time Markov Chains • Introduction, • Classification of States, • Markov Reward Processes, • Time- Reversible Markov Chains, • Semi-Markov Chains • Continuous-Time Markov Chains • Introduction, • Birth and Death Processes, • Kolmogorov Differential Equations, • Limiting Probabilities, • Time Reversibility, • Phase-Type Distributions, • Uniformization

5. Prerequisite • Introduction to Probability • Queueing Theory (would be better)

6. Text Books • Ross, S.M., “Stochastic Processes”, John Wiley & Sons, Inc., 1996. • Ross, S.M., “Introduction to Probability Models”, Academic Press.

7. Reference Books • Kao, Edward P.C., “An Introduction to Stochastic Processes”, Wadsworth Publishing Company, 1997. • Gallager, Robert G., “Discrete stochastic processes”, Kluwer Academic Publishers, 1996.

8. Grading • Homework: 20% • Midterm Exam 1: 25% • Midterm Exam 2: 25% • Final Exam: 20% • Report: 10%