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Performance Evaluation of Computer Systems

Performance Evaluation of Computer Systems. Instructor: Prof. Krishna Moorthy Sivalingam, Department of Computer Science and Engineering, IIT Madras. The objective of this course is to understand the fundamental concepts of computer system performance evaluation. Topics covered in this course will include introduction to mathematical modeling techniques (Markov Chains, Queuing Theory and Networks of Queues), discrete event simulation modeling, experimental design, workload characterization, measurement of performance metrics, analysis and presentation of results. (from nptel.ac.in)

Lecture 12 - Continuous Time Markov Chain and Queuing Theory

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Lecture 01 - Introduction

Lecture 02 - How to Avoid Common Mistakes

Lecture 03 - Selection of Techniques and Metrics

Lecture 04 - Case Study: Selection of Techniques and Metrics

Lecture 05 - Random Variables and Probability Distributions

Lecture 06 - Probability Distributions I

Lecture 07 - Probability Distributions II

Lecture 08 - Probability Distributions III

Lecture 09 - Stochastic Process

Lecture 10 - Markov Chain

Lecture 11 - Slotted Aloha Protocol Model and Discrete Time Birth Death Process

Lecture 12 - Continuous Time Markov Chain and Queuing Theory

Lecture 13 - Queuing Theory I

Lecture 14 - Queuing Theory II

Lecture 15 - Queuing Theory III

Lecture 16 - Queuing Theory IV

Lecture 17 - Queuing Theory V

Lecture 18 - Queuing Theory VI

Lecture 19 - Queuing Networks I

Lecture 20 - Queuing Networks II

Lecture 21 - Slotted Aloha Markov Model

Lecture 22 - Simulations I

Lecture 23 - Simulations II

Lecture 24 - Simulations III

Lecture 25 - Operational Laws I

Lecture 26 - Operational Laws II

Lecture 27 - Open and Closed Queuing Networks

Lecture 28 - Approximate MVA

Lecture 29 - Convolution Algorithm I

Lecture 30 - Convolution Algorithm II

Lecture 31 - Load Dependent Service Centers

Lecture 32 - Hierarchical Decomposition

Lecture 33 - Balanced Job Bounds

Lecture 34 - Confidence Interval for Proportions and Introduction to Experimental Design

Lecture 35 - 2k Factorial Design

Lecture 36 - 2k r Factorial Design and 2k-p Fractional Factorial Design

Lecture 37 - Programming Aspects of Discrete-Event Simulations I

Lecture 38 - Programming Aspects of Discrete-Event Simulations II

Lecture 39 - Discrete-Event Simulations III

Lecture 40 - PetriNets I

Lecture 41 - PetriNets II

Lecture 42 - PetriNets III