ECE 577 - Spring 2009
Computer System and Network Evaluation
Syllabus [click here]
Time and Place
Tuesdays and Thursdays, 9:30-10:45am, Psych. Bldg., Room 304
Instructor
Dr. Marwan Krunz
ECE Building, Room 356H
Phone: (520) 621-8731
Email: (krunz@ece.arizona.edu)
Office Hours
Tuesdays 11am-12pm, Thursdays 2-3pm, and by appointment.
Class Material
There is no required textbook for this class. The material will be based on lecture notes and handouts,
which will either be provided in class or made available through the Copy Center
in Harvill Building.
References:
- Kishor S. Trivedi, Probability and Statistics with Reliability, Queueing and Computer Science
Applications. John Wiley & Sons Inc., 2002 (2nd edition).
- Raj Jain, The Art of Computer Systems Performance Analysis. John Wiley
& Sons, Inc., 1991.
- L. Kleinrock, Queueing Systems -- Volume I: Theory, J. Wiley & Sons, 1975.
- L. Kleinrock, Queueing Systems -- Volume II: Computer Applications,
J. Wiley & Sons, 1976.
- Research papers.
Prerequistes
ECE 503 or an equivalent course in probability theory and random processes
(check with me if you are not sure of the suitability of your background).
Homework Assignments and Solutions
[To be added later]
Course Objectives
Computer systems play a vital role in our lives. The ability to
predict the performance of these systems and optimally design their
parameters is an area of significant interest to computer engineers
and scientists. This course will provide the theoretical
foundation for computer systems analysis and evaluation. With such
foundation, students will learn how to model and evaluate memory systems, CPUs,
network systems, switches, routers, etc. The underlying
principles of computer systems analysis (which are based on
stochastic theory, statistics,
and queueing theory) will be studied. Several operational laws that are
used in analyzing large computer systems will also be discussed.
Topics (tentative):
- Preliminaries: Notation, review of basic concepts in random processes, important theorems,
transform methods, random sums, distribution of failure times, reliability analysis, etc..
- Traffic characterization:
- Elementary traffic models
- Advanced traffic models (Markov models, fluid models, modulated processes, self-similar
processes, etc.).
- Models for multimedia traffic.
- Elementary queueing theory.
- Advanced queueing theory (M/G/1 queue, G/M/1 queue, G/G/1 queue).
- Heavy-traffic approximation.
- Networks of queues: Jackson's networks, open and closed-loop networks.
- Analysis of priority scheduling and queueing systems.
- Fluid analysis.
- Effective bandwidth theory.
- Bounds and approximations.
- Operational laws.
- Workload characterization techniques.
- Mean value analysis (MVA).
- Art of data analysis and representation.
- Statistical techniques: Confidence intervals, analysis of variance, linear and nonlinear regression, etc.
- Analysis of web caching and prefetching systems.
- Other topics (if time permits).
The above topics will be discussed in the context of computer applications (network protocols,
memory systems, capacity analysis, etc.). Examples of related applications will be presented
throughout the course.
Discrete-Event Simulation Using Csim
Although simulations is not the main focus of this course, in some homework assignments you will
be asked to write simulation code and run experiments using the Csim package. The purpose of these
simulations is to study the performance of certain complicated queueing systems that are hard to analyze or to validate
analytical results by comparing them with simulations. I will spend 2-3 lectures reviewing Csim, but you may want to get a
head-start by learning this package on your own before I cover it in class. The full documentation of Csim (including the
User's
Guide and Reference Manual) can be found online at
Mesquite's website (check under
'Documentation').
Grading:
| Homework | | | 25% |
| Quizzes and Class Participation | | | 10% |
| 1st Midterm Exam (tentatively on Thursday, Feb. 19) | | | 20%
|
| 2nd Midterm Exam (tentatively on Thursday, April 9) | | | 20%
|
| Final Exam (Thursday, May 14, 8-10am) | | | 25% |