Slides and Videos
The video lectures can be ordered on a DVD directly from VU's bookstore or can be seen on Youtube through the links below or through this playlist.
Lecture 1: Course introduction (1 lecture) [slides] [video]
Part-1: The Science and Art of Network Performance Evaluation (12 lectures)
Part 1A: Lecture 2 to 4 (3 lectures): The Science of NPE
Lecture 2: The science of performance evaluation [slides] [video]
Lecture 3: Common NPE errors [slides] [video]
Lecture 4: NPE techniques and metrics [slides] [video]
Part 1B: Lecture 5 to 8 (6 lectures): Statistical background (grammar of the science of NPE)
Lecture 5 : Introduction to statistics [slides] [video]
Lecture 6 : Summarizing measured data [slides] [video]
Lecture 7: Sampling a Population [slides] [video]
Lecture 8: Hypothesis testing [slides] [video]
Lecture 9: Confidence Intervals [slides] [video]
Lecture 10: Model fitting or Regression models [slides] [video]
Part 1C: Lecture 11 to 13 (3 lectures): The Art of NPE
Lecture 11 : The art of modeling and performance evaluation [slides] [video]
Lecture 12: Lies, Damned Lies and Statistics [slides] [video]
Lecture 13: How to present quantitative data visually? [slides] [video]
Part-2: Experimental/ Empirical Network Performance Evaluation (11 lectures)
Lecture 14: Introduction to empirical science and to the concept of measurement [slides] [video]
Part 2A: Lecture 15 to 17 (3 lectures): Workload Characterization
Lecture 15: Workload Characterization Techniques [slides] [video]
Lecture 16 Common Distributions (Mediocristan) [slides] [video]
Lecture 17: Common Distributions (Extremistan) [slides] [video]
Lecture 18 Introduction to Fractals [slides] [video]
Lecture 19: Self-Similarity and Long-Range-Dependence (LRD) [slides] [video]
Part 2B: Lecture 18 to 21 (4 lectures): Design of Experiments
Lecture 20: Experimental Design [slides] [video]
Lecture 21: One-Factor Experiments [slides] [video]
Lecture 22: Full Factorial Design [slides] [video]
Lecture 23 Fractional Factorial Design [slides] [video]
Part 2C: Lecture 22 to 24 (3 lectures): Internet Measurement and Empirical Case Studies
Lecture 24: Network Management [slides] [video]
Lecture 25: Internet Measurement Issues and Tools [slides] [video]
Lecture 26: Internet Measurement Results [slides] [video]
Part-3: Modeling and Simulation based Network Performance Evaluation (20 lectures)
Part 3A: Lecture 25 to 28 (6 lectures): Mathematical preliminaries (Probability)
Lecture 27: Introduction to Stochastic Processes [slides] [video]
Lecture 28: Common Stochastic Processes [slides] [video]
Lecture 29 Continuous-Time Markov Chains (CTMCs) [slides] [video]
Lecture 30: DIscrete-Time Markov Chains (DTMCs) [slides] [video]
Part 3B: Lecture 29 to 37 (7 lectures): Analytical modeling
Lecture 31: Introduction to Queuing Theory [slides] [video]
Lecture 32: Fundamentals of Queueing Theory [slides] [video]
Lecture 33: Single-Server Queues [slides] [video]
Lecture 34: Multiple-Server Queues [slides] [video]
Lecture 35: Queueing Networks [slides] [video]
Lecture 36: Operational Analysis [slides] [video]
Lecture 37: Analysis of Queueing Networks [slides] [video]
Part 3C: Lecture 38 to 44 (7 lectures): Simulation modeling
Lecture 38: Introduction to Simulation [slides] [video]
Lecture 39: Random Number Generation [slides] [video]
Lecture 40: Verification and Validation [slides] [video]
Lecture 41: Input Modeling [slides] [video]
Lecture 42: Output Analysis [slides] [video]
Lecture 43: Comparing Systems [slides] [video]
Lecture 44: Simulation Tools [slides] [video]
Lecture 45: Course summary/ conclusions [slides] [video]