CS681/CS 462: Performance Evaluation of Computer Systems and Networks

Spring Semester, 2009


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Course List for CS 681

Course Information

Instructor: Varsha Apte, CSE, IITB (varsha[AT]cse.iitb.ac.in, IIT extn: 7731)

Lecture Schedule: Monday: 02:00pm to 03:25pm, Thursday: 02:00pm to 03:25pm

Office Hours: Wednesdays 2-4pm.

Teaching Assistants: Sanket Dhopeshwarkar,  Piyush Masrani

Evaluation Scheme: For CS 681: 35% End Sem, 20% Midsem, 10% Homework, 25% simulation project, 10% quizes. There will be two quizzes (one before and one after midsem). There will be some homeworks. We will correct random questions out of the given homeworks.
For CS 462: 40% End Sem, 30% Midsem, 10% Homework, 10% simulation assignment, 10% quizes. There will be two quizzes (one before and one after midsem). There will be some homeworks. We will correct random questions out of the given homeworks.

Prerequisites:

Basic familiarity with: Operating Systems (preferably also Networks), Probability and Statistics. Basic implementation skills in a programming language, and scripting language. Equivalent to courses MA212 and CS447

Also, try this pre-requisite quiz, which gives you a flavor of the course.

Who can take this course?

The CS 681 course is for Post-graduate students (M.Tech., M.S., Ph.D.), and DD students.

Requirements for students auditing: project not required, homeworks not required. Evaluation is based on End-sem, Mid-sem, 2 quizes (50%, 40%, 10%), or End-sem (50%), simulation project (50%). Nearly 100% attendance is required for auditing students.

I am generally open to research scholars/project staff or anybody who wants to "sit in" through the course. However, I will not evaluate them. (Please just inform me if you are going to audit or sit-in.)

Course Calendar - 2008

Course Description

This course is a first course on performance evaluation covering the basics of three main evaluation techniques: Measurement, Simulation, and Analytical Modeling. The main focus will be analytical modeling - probability models, Markov models, Queueing models. The course will involve extensive use of mathematical skills. There will be a few simulation and (possibly) measurement assignments, which involve minor programming. The mathematics needed is a basic knowledge of Probability and Statistics. A brief refresher in probability will be done (combination of self-study+lectures) initially.

The course is about evaluating computer systems and networks, so knowing about systems (operating systems) and networks is useful. In case of networks, knowledge of details of data networking protocols will not be assumed (protocol will be introduced, then analyzed), however, absolute basics of networking should be known. In case of systems, familiarity with basic OS mechanisms (e.g. paging, CPU scheduling etc) will be assumed.

The evaluation will include some programming assignments in performance measurement and in simulation modeling, but mostly quizes/homework in analytical modeling. In other words, to do this course you should like to model systems by deriving and solving mathematical equations, as well as learning about various phenomena empirically (with measurement and simulation experiments).

Course contents

Specific topics: Introduction to performance measures, basic probability review, Markov chains, basic queueing models, introduction to simulation modeling, some advanced queueing models, basic queueing networks, examples from papers.