Introduction to Computer System Performance Evaluation

In this book, Krishna Kant provides a completely up-to-date treatment of the fundamental techniques of computer system performance modeling and evaluation. He discusses measurement, simulation, and analysis, and places a strong emphasis on analysis by including such topics as basic and advanced queuing theory, product orm networks, aggregation, decomposition, performance bounds, and various forms of approximations. Applications involving synchronization between various activities are presented in a chapter on Petri net-based performance modeling, and a final chapter covers a wide range of problems involving steady state analysis, transient analysis, and optimization.

• Part I: Basic Concepts
1. Performance Measures and Evaluation Techniques
1. Evaluation Metrics
2. Techniques of Performance Evaluation
3. Applications of Performance Metrics
4. Workload Characterization
5. Benchmarking Computer Systems
6. Exercises
2. Measurement Techniques
1. Classification of Measurement Techniques
2. Hardware Monitoring
3. Software Monitoring
4. Hybrid Monitoring
5. Other Issues in Measurement
6. Exercises
3. Experiment Design and Data Analysis
1. Simulation Techniques
2. Fundamentals of Data Analysis
3. Organizing Simulation Runs
4. Selection of Inputs
5. Comparison of Alternate Designs
6. Regression Analysis
7. Variance Reduction Techniques
8. Exercises
4. Fundamentals of Queuing Models
1. Structure and Performance Parameters
2. Operational Analysis of Queuing Models
3. General Features of Queuing Models
4. Analysis of Multiple-Class Networks
5. Calibration of Queuing Models
6. Exercises
5. Elementary Stochastic Analysis
1. Random Processes
2. Analysis of Markov Chains
3. Long-Term Behavior of Markov Chains
4. Birth and Death Processes
5. Steady-State Analysis of M/M Systems
6. Batch Systems and Methods of Stages
7. Exercises
6. Product-Form Queuing Network Models
1. Characteristics of Product-Form Solutions
2. Open Queuing Network Models
3. Closed Product-Form Networks
4. Multiple-Class Networks
5. Algorithms for Closed PF Networks
6. Conditions for Product-Form Solution
7. Exercises
7. Basic Algorithms for Product-Form Networks
1. Single-Chain Convolution
2. Single-Chain Mean Value Analysis
3. Multiple-Chain Convolutions
4. Multiple-Chain Mean Value Analysis
5. The LBANC Algorithm
6. Algorithms for Mixed Networks
7. Approximate Mean Value Analysis
8. Exercises
8. Aggregation and Approximate Modeling
1. Flow-Equivalent Aggregation
2. Applications of Aggregation
3. Modeling Non-PF Scheduling Disciplines
4. Decomposition Approximations
5. Exercises
• Part II: Advanced Topics
9. Advanced Stochastic Analysis
1. Solution Using Generating Functions
2. Some Results on General Queuing Systems
3. The M/G/1 Queuing System
4. Phase-Type Distributions
5. Matrix-Analytic Methods
6. Additional Topics
7. Exercises
10. Algorithms for Networks with Specialized Features
1. Networks with Advanced Features
2. Chain-Based Recursion Algorithms
3. Algorithms Exploiting Sparsity
4. Asymptotic Expansions
5. Exercises
11. Bounds on Performance
1. Bounds on Single-Chain Networks
2. Networks with Load-Dependent Stations
3. Bounds on Mean Queue Lengths
4. Bounds for Multiple-Chain Networks
5. Exercises
12. Petri Net-Based Performance Modeling
1. Classical Petri Nets
2. Timed Petri Nets
3. Generalized Stochastic Petri Nets
4. Discrete Time Petri Nets
5. Modeling Multiprocessor Systems
6. Extensions to Stochastic Petri Nets
7. Product-Form Solutions
8. Exercises
13. Selected Applications
1. Analysis of Polling Systems
2. Problems in Performance Optimization
3. Analysis of Jobs with Internal Concurrency
4. Modeling Fault-Tolerant Systems
5. Exercises
• Part III: Appendices
1. Notation
2. Introduction to probability Theory
1. Basic Concepts
1. Events and the Probability Measure
2. Random Variables and Distributions
3. Functions of a Random Variable
4. Expectation and Moments
5. Some Inequalities
2. Summary of Selected Distributions
1. Discrete Distributions
2. Continuous Distributions
3. Characteristic Functions
1. The Z-Transform
2. LaPlace Transform
3. General Characteristic Function
4. Exercises
3. A Suggested Modeling Project
1. Project Overview
2. Operational Details of SYS-A
1. Hardware Configuration
2. System Operation
3. Model Construction
1. Model Description
2. Modeling of Minor Overheads
3. Model Calibration and Validation
4. Modeling Enhancements
4. Performance Tuning Using Solver
1. Overview of Solver
2. Tuning a Paging System
1. The Solver Program
2. Interpretation of Results
3. Issues for Further Study
3. Program Listing and Output
5. Selected Tables
1. Critical Points of t Distribution
2. Selection among Alternate Designs
3. Selected LaPlace Transform Pairs
4. Selected z-Transform Pairs

If this is the introduction, I don't want to read an advanced book.

You need a Ph.D. in Computer Science and at least a M.Sc. in Mathematics to understand what he is talking about. It may be an excellent book, but I have no way of knowing. Someone call me and tell me…