UWO, Department of Statistical and Actuarial Sciences,

Stat. 760a: Networks and Queues

Course Outline

Instructor: Zinovi Krougly, WSC 205, (519) 661-2111 ext. 86985,

Course Schedule: Tu 4:00 - 5:30p.m., WSC 248, Th 4:00 - 5:30p.m., WSC 156

Office Hours: Tu Th 2:00 - 3:30 p.m. or by appointment

TEXT: G. Bolch, S. Greiner, H. DeMeer and K. Trivedi, Queuing Networks and Markov Chains: Modeling and Performance Evaluation with Computer Science Applications, John Wiley and Sons, 1998. A copy of the textbook is being purchased by the Taylor library and will be held on a 2-hours reserve basis.

REFERENCES:

S. Ross, Introduction to Probability Models, 7th (or 6th) edition, Academic Press, 2000.
E. Lazowska, J. Zahorjan, G. Graham, and K. Sevcik, Quantitative System Performance - Computer System Analysis Using Queueing Network Models, Prentice-Hall, 1984.
D. Gross, C. Harris, Fundamentals of Queueing Theory , 3rd edition, John Wiley and Son, 1998.
L. Kleinrock, Queueing Systems, V.2: Computer Application, John Wiley and Son, 1976.
D. Menasce , V. Almeida, Scaling for E-Business: Technologies, models, performance, and capacity planning, Prentice Hall, 2000.

COURSE DESCRIPTION:

This course focuses on exact and approximation techniques for the performance evaluation of computer, communication and manufacturing systems, Web-based Internet and Local Area Networks. I will provide computer modeling examples, statistical evaluation of analytical and simulation results.

Course Outline by Topical Areas:

1. Introduction.

2. Queuing network models: preliminary exact results

Jackson networks
Gordon-Newell networks
Applications in computer –communication networks

3. Product-form networks

Single class closed networks
Multiple class networks
Mixed networks
Networks with load dependant service
BCMP networks
Mean value analysis

4. Approximation algorithms for product-form and non-product-form networks

Norton’s theorem, decomposition and approximation technique
Priority models
Priority shadow CPU model

5. Implementation iterations and other numerical techniques

6. Statistical evaluation of analytical and simulation results.

GRADING:

Midterm Exam (30%), two Assignments (10% each) and either a Final Exam (50%) or a Project (50%), to be determined after consultation with students registered in the course.