Introduction to Computer Performance Modeling
ECE/CSC/OR 579, Spring 2018

General Information

Course Moodle Website


The aim of this course is to present queueing theory and simulation techniques as tools for modeling and studying the performance of communication networks and computer systems. The students will be introduced to classical tools and methodology in probability theory and stochastic modeling as well as simulation techniques, all of which are essential tools for students to conduct advanced research in the area of network performance modeling and analysis.

Students will participate and learn by doing assignments before coming to class, by asking and answering questions during in-class discussions, by performing simulation projects, and by preparing for in-class exams.

At the end of this course, students should be able to

  1. Apply simulation techniques to develop models of computer and communication systems
  2. Apply queueing-based models to characterize computer and communication systems
  3. Use appropriate analytic tools to compute performance measures of interest (e.g., delay, throughput) for a given queueing system
  4. Design (or choose) the system parameters (e.g., server or link capacity) to achieve a given level of performance
  5. Evaluate the relative merits of alternative system design solutions
  6. Engage in research in the field of performance analysis and evaluation via Markov chains for general networked systems

Time and Place

 Mon &Wed., 11:45AM--1:00PM, 1010 EB1


Do Young Eun, Professor
Office: 3064 EB2
Phone: 919-513-7406


Office hours: Mon. 2--3PM & Wed. 10:30AM--11:30AM (or by appointment) in 3064 EB2       

Teaching Assistant: TBA


References (on Reserve in the Hunt Library)


Grading (Tentative)

There will be one midterm exam, one final exam, projects (simulation), and homework assignments.

Homework: 20%

Simulation Projects: 15%
Midterm exam: 25%
Final exam: 40%

Note: All exams will be open books and open notes.

Homework grading


Audit students must earn a B average on the homeworks.

Exam Schedule

Midterm Exam: TBA

Final Exam: May 4 (Friday), 8:00 -- 11:00 AM in class (1010 EB1)

Course Policies

Tentative course structure

  1. Review of probability theory and random variables
  2. Review of z-transforms and Laplace transforms
  3. Poisson processes
  4. Markov Chains (both continuous and discrete time)
  5. Birth-Death Processes
  6. M/M/1 queue and variants
  7. M/Er/1, Er/M/1, and Erlang distribution
  8. M/G/1 queue, P-K formular
  9. Priority queueing
  10. Finite State Markov Chains
  11. Other aspects of Performance analysis on networked system and applications (random walk on graph, dynamics on network, Markov Chain Monte Carlo, etc.), if time permits

Students with disabilities

Reasonable accommodations will be made for students with verifiable disabilities. In order to take advantage of available accommodations, students must register with Disability Services for Students. See for more information. more information on NC State's policy on working with students with disabilities, please see

Academic integrity

All the provisions of the NC State University's Code of Student Conduct and University Policy on Academic Integrity apply to this course. In addition, it is my understanding and expectation that your signature on any test or assignment means that you neither gave nor received unauthorized aid.