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9781848217478 |
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9781119006190 |
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electronic bk |
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1119006198 |
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9781119006213 |
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111900621X |
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1848217471 |
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9781322950181 (MyiLibrary) |
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1322950180 (MyiLibrary) |
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(OCoLC)902804402 |
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eng |
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TK5105.5 |
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COM |
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013000 |
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004/.36 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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Chen, Ken |
| Titles and other words associated with a name |
(Engineer), |
| Authority record control number |
http://id.loc.gov/authorities/names/no2014077579 |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
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| Title |
Performance evaluation by simulation and analysis with applications to computer networks / |
| Statement of responsibility, etc |
Ken Chen. |
| 264 #1 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Place of publication, distribution, etc |
London, UK : |
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ISTE, Ltd. ; |
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Hoboken, NJ : |
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Wiley, |
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2015. |
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1 online resource. |
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computer |
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online resource |
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rdacc |
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http://rdaregistry.info/termList/RDAColourContent/1003. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references and index. |
| 505 0# - CONTENTS |
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| Formatted contents note |
Table of Contents<br/>LIST OF TABLES xv<br/><br/>LIST OF FIGURES xvii<br/><br/>LIST OF LISTINGS xxi<br/><br/>PREFACE xxiii<br/><br/>CHAPTER 1. PERFORMANCE EVALUATION 1<br/><br/>1.1. Performance evaluation 1<br/><br/>1.2. Performance versus resources provisioning 3<br/><br/>1.2.1. Performance indicators 3<br/><br/>1.2.2. Resources provisioning 4<br/><br/>1.3. Methods of performance evaluation 4<br/><br/>1.3.1. Direct study 4<br/><br/>1.3.2. Modeling 5<br/><br/>1.4. Modeling 6<br/><br/>1.4.1. Shortcomings 6<br/><br/>1.4.2. Advantages 7<br/><br/>1.4.3. Cost of modeling 7<br/><br/>1.5. Types of modeling 8<br/><br/>1.6. Analytical modeling versus simulation 8<br/><br/>PART 1. SIMULATION 11<br/><br/>CHAPTER 2. INTRODUCTION TO SIMULATION 13<br/><br/>2.1. Presentation 13<br/><br/>2.2. Principle of discrete event simulation 15<br/><br/>2.2.1. Evolution of a event-driven system 15<br/><br/>2.2.2. Model programming 16<br/><br/>2.3. Relationship with mathematical modeling 18<br/><br/>CHAPTER 3. MODELING OF STOCHASTIC BEHAVIORS 21<br/><br/>3.1. Introduction 21<br/><br/>3.2. Identification of stochastic behavior 23<br/><br/>3.3. Generation of random variables 24<br/><br/>3.4. Generation of U(0, 1) r.v. 25<br/><br/>3.4.1. Importance of U(0, 1) r.v. 25<br/><br/>3.4.2. Von Neumann’s generator 26<br/><br/>3.4.3. The LCG generators 28<br/><br/>3.4.4. Advanced generators 31<br/><br/>3.4.5. Precaution and practice 33<br/><br/>3.5. Generation of a given distribution 35<br/><br/>3.5.1. Inverse transformation method 35<br/><br/>3.5.2. Acceptance–rejection method 36<br/><br/>3.5.3. Generation of discrete r.v. 38<br/><br/>3.5.4. Particular case 39<br/><br/>3.6. Some commonly used distributions and their generation 40<br/><br/>3.6.1. Uniform distribution 41<br/><br/>3.6.2. Triangular distribution 41<br/><br/>3.6.3. Exponential distribution 42<br/><br/>3.6.4. Pareto distribution 43<br/><br/>3.6.5. Normal distribution 44<br/><br/>3.6.6. Log-normal distribution 45<br/><br/>3.6.7. Bernoulli distribution 45<br/><br/>3.6.8. Binomial distribution 46<br/><br/>3.6.9. Geometric distribution 47<br/><br/>3.6.10. Poisson distribution 48<br/><br/>3.7. Applications to computer networks 48<br/><br/>CHAPTER 4. SIMULATION LANGUAGES 53<br/><br/>4.1. Simulation languages 53<br/><br/>4.1.1. Presentation 53<br/><br/>4.1.2. Main programming features 54<br/><br/>4.1.3. Choice of a simulation language 54<br/><br/>4.2. Scheduler 56<br/><br/>4.3. Generators of random variables 57<br/><br/>4.4. Data collection and statistics 58<br/><br/>4.5. Object-oriented programming 58<br/><br/>4.6. Description language and control language 59<br/><br/>4.7. Validation 59<br/><br/>4.7.1. Generality 59<br/><br/>4.7.2. Verification of predictions 60<br/><br/>4.7.3. Some specific and typical errors 61<br/><br/>4.7.4. Various tests 62<br/><br/>CHAPTER 5. SIMULATION RUNNING AND DATA ANALYSIS 63<br/><br/>5.1. Introduction 63<br/><br/>5.2. Outputs of a simulation 64<br/><br/>5.2.1. Nature of the data produced by a simulation 64<br/><br/>5.2.2. Stationarity 65<br/><br/>5.2.3. Example 66<br/><br/>5.2.4. Transient period 68<br/><br/>5.2.5. Duration of a simulation 69<br/><br/>5.3. Mean value estimation 70<br/><br/>5.3.1. Mean value of discrete variables 71<br/><br/>5.3.2. Mean value of continuous variables 72<br/><br/>5.3.3. Estimation of a proportion 72<br/><br/>5.3.4. Confidence interval 73<br/><br/>5.4. Running simulations 73<br/><br/>5.4.1. Replication method 73<br/><br/>5.4.2. Batch-means method 75<br/><br/>5.4.3. Regenerative method 76<br/><br/>5.5. Variance reduction 77<br/><br/>5.5.1. Common random numbers 78<br/><br/>5.5.2. Antithetic variates 79<br/><br/>5.6. Conclusion 80<br/><br/>CHAPTER 6. OMNET++ 81<br/><br/>6.1. A summary presentation 81<br/><br/>6.2. Installation 82<br/><br/>6.2.1. Preparation 82<br/><br/>6.2.2. Installation 83<br/><br/>6.3. Architecture of OMNeT++ 83<br/><br/>6.3.1. Simple module 84<br/><br/>6.3.2. Channel 85<br/><br/>6.3.3. Compound module 85<br/><br/>6.3.4. Simulation model (network) 85<br/><br/>6.4. The NED langage 85<br/><br/>6.5. The IDE of OMNeT++ 86<br/><br/>6.6. The project 86<br/><br/>6.6.1. Workspace and projects 87<br/><br/>6.6.2. Creation of a project 87<br/><br/>6.6.3. Opening and closing of a project 87<br/><br/>6.6.4. Import of a project 88<br/><br/>6.7. A first example 88<br/><br/>6.7.1. Creation of the modules 88<br/><br/>6.7.2. Compilation 92<br/><br/>6.7.3. Initialization 92<br/><br/>6.7.4. Launching of the simulation 93<br/><br/>6.8. Data collection and statistics 93<br/><br/>6.8.1. The Signal mechanism 94<br/><br/>6.8.2. The collectors 95<br/><br/>6.8.3. Extension of the model with statistics 95<br/><br/>6.8.4. Data analysis 98<br/><br/>6.9. A FIFO queue 98<br/><br/>6.9.1. Construction of the queue 98<br/><br/>6.9.2. Extension of MySource 101<br/><br/>6.9.3. Configuration 103<br/><br/>6.10. An elementary distributed system 105<br/><br/>6.10.1. Presentation 105<br/><br/>6.10.2. Coding 107<br/><br/>6.10.3. Modular construction of a larger system 114<br/><br/>6.10.4. The system 115<br/><br/>6.10.5. Configuration of the simulation and its scenarios 115<br/><br/>6.11. Building large systems: an example with INET 117<br/><br/>6.11.1. The system 117<br/><br/>6.11.2. Ethernet card with LLC 119<br/><br/>6.11.3. The new entity MyApp 121<br/><br/>6.11.4. Simulation 125<br/><br/>6.11.5. Conclusion 126<br/><br/>PART 2. QUEUEING THEORY 129<br/><br/>CHAPTER 7. INTRODUCTION TO THE QUEUEING THEORY 131<br/><br/>7.1. Presentation 131<br/><br/>7.2. Modeling of the computer networks 133<br/><br/>7.3. Description of a queue 133<br/><br/>7.4. Main parameters 135<br/><br/>7.5. Performance indicators 136<br/><br/>7.5.1. Usual parameters 136<br/><br/>7.5.2. Performance in steady state 136<br/><br/>7.6. The Little’s law 137<br/><br/>7.6.1. Presentation 137<br/><br/>7.6.2. Applications 138<br/><br/>CHAPTER 8. POISSON PROCESS 141<br/><br/>8.1. Definition 141<br/><br/>8.1.1. Definition 141<br/><br/>8.1.2. Distribution of a Poisson process 142<br/><br/>8.2. Interarrival interval 143<br/><br/>8.2.1. Definition 143<br/><br/>8.2.2. Distribution of the interarrival interval Δ 144<br/><br/>8.2.3. Relation between N(t) and Δ 145<br/><br/>8.3. Erlang distribution 145<br/><br/>8.4. Superposition of independent Poisson processes 146<br/><br/>8.5. Decomposition of a Poisson process 147<br/><br/>8.6. Distribution of arrival instants over a given interval 150<br/><br/>8.7. The PASTA property 151<br/><br/>CHAPTER 9. MARKOV QUEUEING SYSTEMS 153<br/><br/>9.1. Birth-and-death process 153<br/><br/>9.1.1. Definition 153<br/><br/>9.1.2. Differential equations 154<br/><br/>9.1.3. Steady-state solution 156<br/><br/>9.2. The M/M/1 queues 158<br/><br/>9.3. The M/M/∞ queues 160<br/><br/>9.4. The M/M/m queues 161<br/><br/>9.5. The M/M/1/K queues 163<br/><br/>9.6. The M/M/m/m queues 164<br/><br/>9.7. Examples 165<br/><br/>9.7.1. Two identical servers with different activation thresholds 165<br/><br/>9.7.2. A cybercafe 167<br/><br/>CHAPTER 10. THE M/G/1 QUEUES 169<br/><br/>10.1. Introduction 169<br/><br/>10.2. Embedded Markov chain 170<br/><br/>10.3. Length of the queue 171<br/><br/>10.3.1. Number of arrivals during a service period 172<br/><br/>10.3.2. Pollaczek–Khinchin formula 173<br/><br/>10.3.3. Examples 175<br/><br/>10.4. Sojourn time 178<br/><br/>10.5. Busy period 179<br/><br/>10.6. Pollaczek–Khinchin mean value formula 181<br/><br/>10.7. M/G/1 queue with server vacation 183<br/><br/>10.8. Priority queueing systems 185<br/><br/>CHAPTER 11. QUEUEING NETWORKS 189<br/><br/>11.1. Generality 189<br/><br/>11.2. Jackson network 192<br/><br/>11.3. Closed network 197<br/><br/>PART 3. PROBABILITY AND STATISTICS 201<br/><br/>CHAPTER 12. AN INTRODUCTION TO THE THEORY OF PROBABILITY 203<br/><br/>12.1. Axiomatic base 203<br/><br/>12.1.1. Introduction 203<br/><br/>12.1.2. Probability space 204<br/><br/>12.1.3. Set language versus probability language 206<br/><br/>12.2. Conditional probability 206<br/><br/>12.2.1. Definition 206<br/><br/>12.2.2. Law of total probability 207<br/><br/>12.3. Independence 207<br/><br/>12.4. Random variables 208<br/><br/>12.4.1. Definition 208<br/><br/>12.4.2. Cumulative distribution function 208<br/><br/>12.4.3. Discrete random variables 209<br/><br/>12.4.4. Continuous random variables 210<br/><br/>12.4.5. Characteristic function 212<br/><br/>12.5. Some common distributions 212<br/><br/>12.5.1. Bernoulli distribution 212<br/><br/>12.5.2. Binomial distribution 213<br/><br/>12.5.3. Poisson distribution 213<br/><br/>12.5.4. Geometric distribution 214<br/><br/>12.5.5. Uniform distribution 215<br/><br/>12.5.6. Triangular distribution 215<br/><br/>12.5.7. Exponential distribution 216<br/><br/>12.5.8. Normal distribution 217<br/><br/>12.5.9. Log-normal distribution 219<br/><br/>12.5.10. Pareto distribution 219<br/><br/>12.6. Joint probability distribution of multiple random variables 220<br/><br/>12.6.1. Definition 220<br/><br/>12.6.2. Independence and covariance 221<br/><br/>12.6.3. Mathematical expectation 221<br/><br/>12.7. Some interesting inequalities 222<br/><br/>12.7.1. Markov’s inequality 222<br/><br/>12.7.2. Chebyshev’s inequality 222<br/><br/>12.7.3. Cantelli’s inequality 223<br/><br/>12.8. Convergences 223<br/><br/>12.8.1. Types of convergence 224<br/><br/>12.8.2. Law of large numbers 226<br/><br/>12.8.3. Central limit theorem 227<br/><br/>CHAPTER 13. AN INTRODUCTION TO STATISTICS 229<br/><br/>13.1. Introduction 229<br/><br/>13.2. Description of a sample 230<br/><br/>13.2.1. Graphic representation 230<br/><br/>13.2.2. Mean and variance of a given sample 231<br/><br/>13.2.3. Median 231<br/><br/>13.2.4. Extremities and quartiles 232<br/><br/>13.2.5. Mode and symmetry 232<br/><br/>13.2.6. Empirical cumulative distribution function and histogram 233<br/><br/>13.3. Parameters estimation 236<br/><br/>13.3.1. Position of the problem 236<br/><br/>13.3.2. Estimators 236<br/><br/>13.3.3. Sample mean and sample variance 237<br/><br/>13.3.4. Maximum-likelihood estimation 237<br/><br/>13.3.5. Method of moments 239<br/><br/>13.3.6. Confidence interval 240<br/><br/>13.4. Hypothesis testing 241<br/><br/>13.4.1. Introduction 241<br/><br/>13.4.2. Chi-square (χ2) test 241<br/><br/>13.4.3. Kolmogorov–Smirnov test 244<br/><br/>13.4.4. Comparison between the χ2 test and the K-S test 246<br/><br/>CHAPTER 14. MARKOV PROCESS 247<br/><br/>14.1. Stochastic process 247<br/><br/>14.2. Discrete-time Markov chains 248<br/><br/>14.2.1. Definitions 248<br/><br/>14.2.2. Properties 251<br/><br/>14.2.3. Transition diagram 253<br/><br/>14.2.4. Classification of states 254<br/><br/>14.2.5. Stationarity 255<br/><br/>14.2.6. Applications 257<br/><br/>14.3. Continuous-time Markov chain 260<br/><br/>14.3.1. Definitions 260<br/><br/>14.3.2. Properties 262<br/><br/>14.3.3. Structure of a Markov process 263<br/><br/>14.3.4. Generators 266<br/><br/>14.3.5. Stationarity 267<br/><br/>14.3.6. Transition diagram 270<br/><br/>14.3.7. Applications 272<br/><br/>BIBLIOGRAPHY 273<br/><br/>INDEX 277 |
| 545 0# - BIOGRAPHICAL OR HISTORICAL DATA |
|---|
| Biographical or historical note |
About the Author<br/>An engineer by training, Ken Chen is a professor at the University Paris 13 and professor at Telecom ParisTech. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Computer networks |
| General subdivision |
Evaluation. |
| Authority record control number |
http://id.loc.gov/authorities/subjects/sh2009121224. |
| 655 #4 - INDEX TERM--GENRE/FORM |
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| Genre/form data or focus term |
Electronic books. |
| 655 #7 - INDEX TERM--GENRE/FORM |
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| Genre/form data or focus term |
Electronic books. |
| Source of term |
local. |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
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| Uniform Resource Identifier |
https://onlinelibrary.wiley.com/doi/book/10.1002/9781119006190 |
| Link text |
Full text is available at Wiley Online Library Click here to view |
| 942 ## - ADDED ENTRY ELEMENTS |
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| Source of classification or shelving scheme |
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| Item type |
EBOOK |