E2 204, Spring 2017

Stochastic Processes & Queueuing Theory


Lectures


Homework


  • 10 Jan 2017: Homework 1
  • 24 Jan 2017: Homework 2
  • 07 Feb 2017: Homework 3
  • 21 Feb 2017: Homework 4
  • 07 Mar 2017: Homework 5
  • 21 Mar 2017: Homework 6
  • 04 Apr 2017: Homework 7

Tests


  • 20 Jan 2017: Quiz 1
  • 10 Feb 2017: Quiz 2
  • 17 Feb 2017: Mid Term
  • 20 Mar 2017: Quiz 3
  • 31 Mar 2017: Quiz 4
  • 07 Apr 2017: Quiz 5
  • 14 Apr 2017: Final
  • 17 Apr 2017: Take-home
  • 29 Apr 2017: Project

Grading Policy


Mid Term: 20
Homework: 20
Project : 20
Final : 40

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.

Slack/GitHub Information


Slack

Students can signup for slack using their ece.iisc.ernet.in email at Slack signup.

GitHub

All the students in the class have read access to Stochastic-Processes public repository on GitHub.

Instructors


Aditya Gopalan
Office: ECE 2.09

Parimal Parag Office: ECE 2.17

Time and Location


Classroom: ECE 1.07, Main ECE Building
Hours: Tu/Th 05:00 pm - 06:30 pm.

Teaching Assistants


TBD

Textbooks


Stochastic Processes, Sheldon M. Ross, 2nd edition, 1996.

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