E2 204, Spring 2023

Stochastic Processes & Queueuing Theory




Quiz Hours: 10:00-10:30am
Test Hours: 10:00am-01:00pm
Venue: EC 1.07

  • 21 Jan 2023: Quiz 1
  • 04 Feb 2023: Quiz 2
  • 18 Feb 2023: Mid Term 1
  • 04 Mar 2023: Quiz 3
  • 18 Mar 2023: Quiz 4
  • 01 Apr 2023: Mid Term 2
  • 15 Apr 2023: Quiz 5
  • 22 Apr 2023: Quiz 6
  • 26 Apr 2023: Final (09:00am-01:00pm)

Grading Policy

Quizzes: 30
Mid Terms: 40
Final: 30

Course Syllabus

Poisson process, Renewal theory, Markov chains, Reversibility, Queueing networks, Martingales, Random walk.

Course Description

Basic mathematical modeling is at the heart of engineering. In both electrical and computer engineering, many complex systems are modeled using stochastic processes. This course will introduce students to basic stochastic processes tools that can be utilized for performance analysis and stochastic modeling of dynamic systems and networks.

Teams/GitHub Information


We will use Microsoft Teams for all the course related communication.
Please do not send any email regarding the course.
You can signup for the course team Stochastic-Processes-2023 using the following code pi3h8to.


All the students in the class have read access to Stochastic-Processes public repository on GitHub.
Please follow the guidelines in the sample lecture.
The source file for the sample lecture is in the repository.
It is recommended you save it with another name in your local repository for creating a new lecture.
Here is a good book for Git and a simple tutorial.


Parimal Parag
Office: EC 2.17
Hours: By appointment.

Time and Location

Classroom: Auditorium 2, MP 30, ECE MP Building
Hours: Tue/Thu 10:00am-11:30am.

Teaching Assistants

Email: nitika2021@iisc.ac.in
Hours: By appointment.


Stochastic Processes, P. Parag and Vinod Sharma.

Stochastic Processes, Sheldon M. Ross, 2nd edition, 1996. You can get a copy of the textbook from the campus book store.

Stochastic Processes 

Introduction to Stochastic Processes, Erhan Cinlar, 2013.

Introduction to Stochastic Processes 

Markov Chains: Gibbs Fields, Monte Carlo Simulation, and Queues, Pierre Bremaud, 1999.

Markov Chains 

Markov Chains, James R. Norris, 1998.

Markov Chains 

Reversibility and Stochastic Networks, Frank P. Kelly, 2011.

Reversibility and Stochastic Networks 

Probability: Theory and Examples, Rick Durett, 4th edition, 2010.

Probability Theory