| Description |
1 online resource (xiv, 102 pages) : illustrations |
| Series |
Synthesis lectures on computer science, 1932-1686 ; #2 |
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Synthesis lectures on computer science ; #2.
|
| Contents |
0. Preliminaries |
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1. Concepts and Little's law -- Concepts -- Open and closed systems -- Little's law -- Discussion |
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2. Single queues -- Applying Little's law to a 1-server queue -- Queue specification -- Pollaczek-Khinchin formula -- Discussion |
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3. Open systems -- Residual life -- Birth-death process -- Open queueing networks: Jackson networks -- Discussion |
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4. Markov chains -- Markov chain for a closed network -- Markov chain for a multi-class network -- State aggregation -- Discussion |
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5. Closed systems -- PASTA -- Arrival theorem -- Mean value analysis (MVA) -- Discussion |
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6. Bottlenecks and flow equivalence -- Bottleneck analysis -- Flow equivalence -- Equivalence between open and closed -- Discussion |
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7. Deterministic approximations -- Average value approximation (AVA) -- Fluid approximation -- Discussion |
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8. Transient analysis -- Decomposing an equilibrium -- Epidemic models -- Discussion |
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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 |
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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 |
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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 93-96) and index |
| Subject |
Computer systems -- Reliability -- Mathematical models
|
| Form |
Electronic book
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| ISBN |
9781608454419 |
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160845441X |
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