UMD Logo

Course Description - CMSC 710, Spring 2001

This course will cover the basic tools necessary for performance evaluation of computer and communication systems (details of specific topics are given below). It is intended as an introduction to techniques needed to construct and analyze performance models that are useful in computer and communication systems design. For instance, such techniques have been used in the design of the Internet, OS scheduling policies, parallel and distributed systems, video-on-demand systems, and many more. Although these techniques are useful in other field (e.g., financial modeling), the course will focus on applications to computer and communication systems.
Who should take this course?
Any student interested in computer and/or communication systems and the related performance issues, especially those interested in operating systems, networking, distributed systems, databases, and multimedia systems. The intent of the course is to provide the tools necessary for evaluating designs of such systems as well as for gaining insights that can be obtained.
Tentative Topics Covered
We will cover the following topics in some detail (as time permits):
  • Brief review of probabilities, random variables, and transforms.
  • Introduction to stochastic processes, including Markov chains.
  • Baby queueing theory.
  • Intermediate queueing theory.
  • Markovian models with special structure, including aggregation techniques, stochastic complementation, matrix geometric structure, and so on.
  • Sample Path Analysis.
  • Transient analysis.
  • Reversibility.
  • Queueing networks, including product form networks, mean value analysis, and so on.
  • Simulation.

Text Books and References
There are no required textbooks at this point ... there maybe some later.

The material will be taken from books and research papers; representative books include:

  • Kleinrock, Queueing Systems, Volume I.
  • Ross, Introduction to Probability Models.
  • Stewart, Introduction to the Numerical Solution of Markov Chains.
We will not, of course, cover all material in these books; they are listed just to give you an idea of the topics covered in this course.
Workload (tentative)
There will be a number of homework assignments and possibly a small projects. The homeworks will be assigned but most likely they will not be graded, i.e., they are for your own good (I will post solutions); they might involve the use of tools such as CSIM, ns2, MATLAB, and so on.

A midterm and a final will be given. Any schedule conflicts involving exam dates must be reported to the instructor within one week of the announcement of the exam date.

Grading (tentative)
  • Homeworks/Project:   20%
  • Midterm:     40%
  • Final:     40%
The weights are approximate and may change by upto 20%.

[Last updated Mon Aug 27 2001]    [Please see copyright regarding copying.]