Semester – Spring 2016
Course Instructor – Prof. Jayakrishnan Nair
Pre-requisites – A basic probability course
EE 325 – Probability and Random Processes or EE 601 – Statistical Signal Analysis (or equivalent course in another dept.)
Motivation for this course –
This course starts right where EE325 ends and takes you deeper into Markov Chains. You will come across a lot of interesting probability riddles throughout the course and even in exams. Professor Nair’s enthusiastic and lucid way of teaching is another factor which makes this course great. Markov chains and Queueing systems have a lot of practical applications (Google Pagerank, Call waiting/dropping at Call centers) which are discussed in the class. The interesting syllabus and enjoyable classes make sure you have a good attendance record (which carries 5% weightage).
Course Content –
As the name suggests, this is a two-part course. The first part covers discrete and continuous time Markov chains and their applications. In the second part, the knowledge of Markov chains is used to study modeling and performance evaluation of queueing systems. The following topics are covered:
- Discrete-time Markov chains
- Introduction to Renewal Reward Theory
- Continuous-time Markov chains
- Markovian queueing models — M/M/1, Erlang B & C
- Phase-type distributions and Matrix Analytic Methods
- M/G/1 mean value analysis via Renewal Reward
- M/G/1 transform analysis
- Scheduling policies in M/G/1: FCFS, LCFS, PLCFS, SRPT
- Burke’s Theorem & Queueing Networks
Lectures –
As mentioned above, the lectures are fun and the teaching is just as good. Professor Nair uploads decent quality class notes of his own, so making your own notes is never a necessity. Attendance and class participation carry marks but are not compulsory. The lectures are well-paced and are never too theoretical or too vague. Some students did find the series of theorems taught initially a bit boring and unnecessary but they are essential and moreover, aren’t asked directly. Only their application is what the course is concerned with.
Exams –
- Homework assignments – 25%
- Quizzes (2) — 20%
- Mid-term – 20%
- End-term – 30%
- Class participation – 5%
The usual pattern of examinations is followed (Quiz in each half-sem, midsem, endsem). The exams are easier than they are tough, with class averages going as high as 60%. Simple application of the concepts taught in the class is asked. 6 assignments were given out over the course of the entire semester. The students are encouraged to discuss but copying can be punished. The difficulty level of exams and assignments is comparable and there is honestly no need of copying anywhere.
Grading –
Grading is pretty lenient, to go with the fairly easy exams. A good attendance, timely submission of assignments and a feel of how to apply the topics taught in class will get you the grade of your dreams.
| AA | 10 |
|---|---|
| AB | 20 |
| AP | 1 |
| AU | 7 |
| BB | 12 |
| BC | 11 |
| CC | 5 |
| CD | 3 |
| DD | 1 |
| FR | 3 |
| Total | 73 |
Review by Utkarsh Sharma (utkarsh.hs@gmail.com)