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| Course Category: |
Computer Science/Information Technology |
| Course Level: |
Graduate |
| Credit Hours: |
3 |
| Pre-requisites: |
CS610MTH101 STA301 |
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Course Synopsis
This is a graduate level course. The purpose of this course is to present a comprehensive breadth-focused overview of empirical, analytical, and simulation techniques used for modeling and studying the performance of communication networks. In particular, following details will be covered: a. Empirical techniques: how to design valid experiments through which we systematically analyze communication networks through measurements? b. Analytical techniques: how to we make analytical models to analyze and model the performance of communication networks? In particular, we will gain an overview of queueing theory and its most important results. c. Simulation techniques: how do we make computational models to analyze and model the performance of communication networks?
Course Learning Outcomes
Upon successful completion of this course, students should be able to:
- Apply simulation techniques to develop valid models of communication networks
- Apply queueing-based models to characterize communication networks and to gain insights about their performance
- Perform measurement-based empirical performance analysis of communication networks
- Design a set of experiments to obtain the most information for a given level of effort
- Understand the inherent trade-offs involved in using simulation, measurement, and analytical modeling
- Avoid common simulation/ modeling/ measurement/ data presentation/ data analysis errors
- Evaluate the relative merits of alternative system/algorithm design solutions
- Present quantitative results visually in an effective manner
- Engage in research in the field of performance analysis and evaluation
Course Contents
Course introduction, The Science of Network Performance Evaluation, Experimental/ Empirical Network Performance Evaluation, The Art of Network Performance Evaluation, Modeling and Simulation based Network Performance Evaluation, Course summary/ conclusions.
Course Related Links
Gallery of Data Visualization The Best and Worst of Statistical Graphics
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| Course Instructor |
Dr. Junaid Qadir Ph.D.
University of New South Wales, Australia
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| Books
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First Course in Design and Analysis of Experiments by Gary W. Oehlert |
Analyzing Computer Systems Performance, With Perl, PDQ by Neil J. Gunther |
Computer Networks and Systems: Queuing Theory & Performance Evaluation by Thomas G. Robertazzi |
Computer Systems Performance Evaluation and Prediction by Paul Fortier, Howard Michel |
Data Networks by Dimitri P. Bertsekas, Gallager |
Fundamentals of Performance Evaluation of Computer and Telecommunications Systems by Mohammed S. Obaidat, Noureddine A. Boudriga |
High Performance TCP/IP Networking by Mahbub Hassan, Raj Jain |
High-Speed Networks and Internets: Performance and Quality of Service by William Stallings |
How to Measure Anything: Finding the Value of Intangibles in Business by Douglas W. Hubbard |
Internet Measurement: Infrastructure, Traffic and Applications by Mark Crovella, Balachander Krishnamurthy |
Measuring Computer Performance: A Practitioner's Guide by David J. Lilja |
Network Performance Toolkit: Using Open Source Testing Tools by Richard Blum |
Simulation Modeling and Analysis with ARENA by Tayfur Altiok, Benjamin Melamed |
The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling by Raj Jain |
The Cartoon Guide to Statistics by Larry Gonick, Woollcott Smith |
Discrete-Event Simulation: A First Course by Lawrence M. Leemis, Stephen K. Park |
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