Description 
1 online resource (xiv, 102 pages) : illustrations 
Series 
Synthesis lectures on computer science, 19321686 ; #2 

Synthesis lectures on computer science ; #2

Contents 
0. Preliminaries 

1. Concepts and Little's law  Concepts  Open and closed systems  Little's law  Discussion 

10. Analysis with an analytical model  The science & art in performance modeling  Power  Technique  Assumptions and approximations  Metrics  Science and technology  Intuition and contradiction  Discussion 

2. Single queues  Applying Little's law to a 1server queue  Queue specification  PollaczekKhinchin formula  Discussion 

3. Open systems  Residual life  Birthdeath process  Open queueing networks: Jackson networks  Discussion 

4. Markov chains  Markov chain for a closed network  Markov chain for a multiclass network  State aggregation  Discussion 

5. Closed systems  PASTA  Arrival theorem  Mean value analysis (MVA)  Discussion 

6. Bottlenecks and flow equivalence  Bottleneck analysis  Flow equivalence  Equivalence between open and closed  Discussion 

7. Deterministic approximations  Average value approximation (AVA)  Fluid approximation  Discussion 

8. Transient analysis  Decomposing an equilibrium  Epidemic models  Discussion 

9. Experimental validation and analysis  Case study: database transaction locking  Model validation and experimental analysis  The need for validation  Data presentation  Real systems and workloads  Simulation  Parameter space reduction  Uninteresting regions of parameter space  Quantitative prediction vs. qualitative understanding  Analytic validation  Discussion 

A. Exercises  Bibliography  Author's biography  Index 
Summary 
This book is an introduction to analytical performance modeling for computer systems, i.e., writing equations to describe their performance behavior. It is accessible to readers who have taken college level courses in calculus and probability, networking, and operating systems. This is not a training manual for becoming an expert performance analyst. Rather, the objective is to help the reader construct simple models for analyzing and understanding the systems in which they are interested. Describing a complicated system abstractly with mathematical equations requires a careful choice of assumptions and approximations. These assumptions and approximations make the model tractable, but they must not remove essential characteristics of the system, nor introduce spurious properties. To help the reader understand the choices and their implications, this book discusses the analytical models in 20 research papers. These papers cover a broad range of topics: processors and disks, databases and multimedia, worms and wireless, etc. An Appendix provides some questions for readers to exercise their understanding of the models in these papers 
Bibliography 
Includes bibliographical references (pages 9396) and index 
Subject 
Computer systems  Reliability  Mathematical models.

Form 
Electronic book

ISBN 
160845441X 

9781608454419 

(paperback) 

(paperback) 
