Advanced Topics in Quality of Service (QoS)
ECE/CSC 791Q, Spring 2004
General Information
Objective
The aim of this course will be to introduce the students to
the issues of Quality of Service (QoS) in highspeed networks as well as the
notion of traffic models and their impact on performance. The focus is on
providing recentlydeveloped techniques for QoS issues in the literature with
sound mathematical backgrounds. The course will help the students engage in
advanced research areas in the network performance analysis and also help
understand and write technical papers in their careers.
Description
Short
Description: (for departmental course listing)
QoS issues in highspeed networks. Introduce advanced
modeling and analysis techniques including network calculus (maxplus algebra),
introduction to large deviation, Gaussian traffic modeling, longrange
dependence, as well as probabilistic limiting results in the literature. A brief
summary of probability measure and various inequalities are also given.
Full Description
QoS issues in highspeed networks are (and still will be)
one of the major challenges in the design of networks, and hence it is critical
that students be taught the methodology and models, which form the basis of
determining QoS. This course will be methodological, and the principal
approaches for calculating and providing QoS will be given. Both the
deterministic as well as statistical approaches to QoS will be covered. To this
aim, this course will start with some covering of basic probability theory
(measuretheoretic). Then, the students will be introduced to tools from
maxplus calculus or network calculus, basic techniques from large deviations
theory and also from various traffic models including the issues of shortrange
and longrange dependence. Applications to admission control and statistical
multiplexing of many sources in networks will also be discussed. Throughout the
course, proofs and intuitive remarks will also be provided to each topic as much
as possible. See the tentative course structure below for more details.
Time and Place
1:05pm  2:20pm Tue. and Thurs.
KAMPHOEFNER
HALL A002Instructor
Prof. Do Young Eun
Office: Daniels 367
Phone: 9195137406
Office hours (in Daniels 367):
Tue 2:30pm  4:00pm
Email: dyeun@eos.ncsu.edu
Prerequisites

ECE 514 or equivalent (a course in probability or statistics),

ECE/CSC
570, *and* ECE/CSC 579 or equivalent.

Other
advanced networking courses such as ECE/CSC 776, 777, etc., are helpful, but
not required.
Exam
There will be no
exam for this course. However, homework assignments and one final
project (essay or report on specific subjects discussed in class) will be
given for this course.
Course Website
http://courses.ncsu.edu/ece791q/lec/001Textbook
No textbook required. Class notes and several references will be used instead.
References
 Mischa Schwartz: Broadband Integrated Networks,
Prentice Hall, 1996
 CS. Chang: Performance Guarantees in Communication
Networks, SpringerVerlag, 1999
 JeanYves Le Boudec:
Network Calculus Book,
SpringerVerlag LNCS 2050, 2002 (This book is available on the Web for
freedownload by the author)
 Dembo and O. Zeitouni: Large Deviations Techniques
and Applications (2^{nd}), SpringerVerlag, 1998
 Class notes and recent papers from the literature
Note: The books
above are not required, and only parts of them will be used in the class. As to
the probability background, some early chapters of the following books will be
useful:

Sheldon Ross: Stochastic
Processes (2^{nd}), John Wiley & Sons, 1996

Patrick
Billingsley: Probability and Measure (3^{rd}), Wiley, 1995

William Feller: An
Introduction to Probability Theory and Its Applications, Volume 1, (3^{rd}),
John Wiley & Sons, 1968

Richard Durrett:
Probability: Theory and Example (2^{nd}), Duxbury Press,
1996
Tentative course structure^{*}
 Probability measure
 BorelCantelli lemma, Convergences
 Law of large numbers and centrallimit theorem (also
Poisson limit theorem)
 Various and useful inequalities in L^{p} space
(e.g., Jensen, Holder, Chernoff, Hoeffding, Minkowski, etc.)
 Fluid queueing models: stability, Loynes’ theorem and
Lindley’s formula
 Deterministic traffic models (traffic envelopes)
 Introduction to network calculus: leakybucket
descriptions (or regulated traffic), I/O properties, etc.
 Endtoend delay in networks via network calculus
 Gaussian traffic models and network implications
 Introduction to large deviations (Why large deviations?)
 Case study: largebuffer asymptotic,
manysourcesasymptotic
 Statistical multiplexing and effective bandwidths, and
Other QoS issues.
 Introduction to the convergence of probability measure
(weak convergence)
Note*:
This is a bit
aggressive and extensive schedule. If this turns out to be too much, it will be
appropriately adjusted during the semester.
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 at 1900
Student Health Center, Campus Box 7509,
5157653.
http://www.ncsu.edu/provost/offices/affirm_action/dss/ For
more information on NC State's policy on working with students with
disabilities, please see
http://www.ncsu.edu/provost/hat/current/appendix/appen_k.html
Academic integrity
All the provisions of the code
of 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.