Description
Book SynopsisThis book is written for computer engineers and scientists active in the development of software and hardware systems. It supplies the understanding and tools needed to effectively evaluate the performance of individual computer and communication systems. It covers the theoretical foundations of the field as well as specific software packages being employed by leaders in the field.
Trade Review… written by a scientist successful in performance evaluation, it is based on his experience and provides many ideas not only to laymen entering the field, but also to practitioners looking for inspiration. The work can be read systematically as a textbook on how to model and test the derived hypotheses on the basis of simulations. Also, separate parts can be studied, as the chapters are self-contained. … the book can be successfully used either for self-study or as a supplementary book for a lecture. I believe that different types of readers will like it: practicing engineers and researchers dealing with new solutions, as well as graduate students starting their adventures in the jungle of performance evaluation.
—Piotr Cholda, in IEEE Communications Magazine, October 2011
Table of ContentsMethodology
What is Performance Evaluation ?
Factors
Evaluation Methods
The Scientific Method
Performance Patterns
Summarizing Performance Data, Confidence Intervals
Summarized Performance Data
Confidence Intervals
The Independence Assumption
Prediction Interval
Which Summarization To Use?
Other Aspects of Confidence/Prediction Intervals
Proofs
Model Fitting
Model Fitting Criteria
Linear Regression
Linear Regression with Norm Minimization
Choosing a Distribution
Heavy Tail
Proofs
Tests
The Neyman Pearson Framework
Likelihood Ratio Tests
ANOVA
Asymptotic Results
Other Tests
Proofs
Forecasting
What is Forecasting ?
Linear Regression
The Overfitting Problem
Differencing the Data
Fitting Differenced Data to an ARMA Model
Sparse ARMA and ARIMA Models
Proofs
Discrete Event Simulation
What is a Simulation?
Simulation Tehniques
Computing the Accuracy of Stochastic Simulations
Monte Carlo Simulation
Random Number Generators
How to Sample from a Distribution
Importance Sampling
Proofs
Palm Calculus, or the Importance of the Viewpoint
An Informal Introduction
Palm Calculus
Other Useful Palm Calculus Results
Simulation Defined as Stochastic Recurrence
Application to Markov Chain Models and the PASTA Property
Appendix: Quick Review of Markov Chains
Proofs
Review Questions
Queuing Theory for Those Who Cannot Wait
Deterministic Analysis
Operational Laws For Queuing Systems
Classical Results for a Single Queue
Definitions for Queuing Networks
The Product-Form Theorem
Computational Aspects
What This Tells Us
Mathematical Details About Product-Form Queuing Networks
Case Study
Proofs
Each chapter concludes with a Review that includes review questions.
