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| 008 | 150205s2015 enk ob 001 0 eng d | ||
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| 020 | _a9781848217478 | ||
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_a004/.36 _223 |
| 049 | _aMAIN | ||
| 100 | 1 |
_aChen, Ken _c(Engineer), _eauthor. _1https://id.oclc.org/worldcat/entity/E39PCjtrVVYDccH8kdwwwBv3pP |
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| 245 | 1 | 0 |
_aPerformance evaluation by simulation and analysis with applications to computer networks / _cKen Chen. |
| 264 | 1 |
_aLondon, UK : _bISTE, Ltd. ; _aHoboken, NJ : _bWiley, _c2015. |
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| 300 | _a1 online resource | ||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 504 | _aIncludes bibliographical references and index. | ||
| 588 | 0 | _aOnline resource; title from PDF title page (John Wiley, viewed February 17, 2015). | |
| 505 | 0 | _aCover -- Title Page -- Copyright -- Contents -- List of Tables -- List of Figures -- List of Listings -- Preface -- 1: Performance Evaluation -- 1.1. Performance evaluation -- 1.2. Performance versus resources provisioning -- 1.2.1. Performance indicators -- 1.2.2. Resources provisioning -- 1.3. Methods of performance evaluation -- 1.3.1. Direct study -- 1.3.2. Modeling -- 1.4. Modeling -- 1.4.1. Shortcomings -- 1.4.2. Advantages -- 1.4.3. Cost of modeling -- 1.5. Types of modeling -- 1.6. Analytical modeling versus simulation | |
| 505 | 8 | _aPART 1: Simulation2: Introduction to Simulation -- 2.1. Presentation -- 2.2. Principle of discrete event simulation -- 2.2.1. Evolution of a event-driven system -- 2.2.2. Model programming -- 2.2.2.1. Scheduler -- 2.2.2.2. Object-oriented programming -- 2.3. Relationship with mathematical modeling -- 3: Modeling of Stochastic Behaviors -- 3.1. Introduction -- 3.2. Identification of stochastic behavior -- 3.3. Generation of random variables -- 3.4. Generation of U(0, 1) r.v. -- 3.4.1. Importance of U(0, 1) r.v. -- 3.4.2. Von Neumann's generator | |
| 505 | 8 | _a3.4.3. The LCG generators3.4.3.1. Presentation -- 3.4.3.2. Properties -- 3.4.3.2.1. MLCG with M = 2k -- 3.4.3.2.2. MLCG with M primer number -- 3.4.3.3. Examples of LCG -- 3.4.4. Advanced generators -- 3.4.4.1. Principle -- 3.4.4.2. Mersenne Twister generator -- 3.4.4.3. L'Ecuyer's generator -- 3.4.5. Precaution and practice -- 3.4.5.1. Nature of the PRNG -- 3.4.5.2. Choice of seed -- 3.4.5.3. Multiples substreams of RNG -- 3.4.5.3.1. Principle -- 3.4.5.3.2. Example of OMNeT++ -- 3.4.5.4. Quality of the PRNG | |
| 505 | 8 | _a3.5. Generation of a given distribution3.5.1. Inverse transformation method -- 3.5.2. Acceptance rejection method -- 3.5.2.1. Case of finite support -- 3.5.2.2. Generalized version -- 3.5.3. Generation of discrete r.v. -- 3.5.3.1. Case of the finite discrete r.v. -- 3.5.3.2. Case of countably infinite discrete r.v. -- 3.5.4. Particular case -- 3.5.4.1. Composition -- 3.5.4.2. Convolution -- 3.6. Some commonly used distributions and their generation -- 3.6.1. Uniform distribution -- 3.6.1.1. Utilization -- 3.6.1.2. Parameters -- 3.6.1.3. Generation | |
| 505 | 8 | _a3.6.2. Triangular distribution3.6.2.1. Utilization -- 3.6.2.2. Parameters -- 3.6.2.3. Generation -- 3.6.3. Exponential distribution -- 3.6.3.1. Utilization -- 3.6.3.1.1. Arrival process -- 3.6.3.1.2. Memoryless phenomena -- 3.6.3.2. Parameter -- 3.6.3.3. Generation -- 3.6.4. Pareto distribution -- 3.6.4.1. Utilization -- 3.6.4.2. Parameters -- 3.6.4.3. Generation -- 3.6.5. Normal distribution -- 3.6.5.1. Utilization -- 3.6.5.2. Parameters -- 3.6.5.3. Generation -- 3.6.6. Log-normal distribution -- 3.6.6.1. Utilization -- 3.6.6.2. Parameters | |
| 520 | _aThis book is devoted to the most used methodologies for performance evaluation: simulation using specialized software and mathematical modeling. An important part is dedicated to the simulation, particularly in its theoretical framework and the precautions to be taken in the implementation of the experimental procedure. These principles are illustrated by concrete examples achieved through operational simulation languages (OMNeT ++, OPNET). Presented under the complementary approach, the mathematical method is essential for the simulation. Both methodologies based largely on the theory of. | ||
| 590 |
_aJohn Wiley and Sons _bWiley Online Library: Complete oBooks |
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| 650 | 0 |
_aComputer networks _xEvaluation. |
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| 650 | 6 |
_aR�eseaux d'ordinateurs _x�Evaluation. |
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| 650 | 7 |
_aCOMPUTERS _xComputer Literacy. _2bisacsh |
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| 650 | 7 |
_aCOMPUTERS _xComputer Science. _2bisacsh |
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| 650 | 7 |
_aCOMPUTERS _xData Processing. _2bisacsh |
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| 650 | 7 |
_aCOMPUTERS _xHardware _xGeneral. _2bisacsh |
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| 650 | 7 |
_aCOMPUTERS _xInformation Technology. _2bisacsh |
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| 650 | 7 |
_aCOMPUTERS _xMachine Theory. _2bisacsh |
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| 650 | 7 |
_aCOMPUTERS _xReference. _2bisacsh |
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| 650 | 7 |
_aComputer networks _xEvaluation _2fast |
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| 758 |
_ihas work: _aPerformance evaluation by simulation and analysis with applications to computer networks (Text) _1https://id.oclc.org/worldcat/entity/E39PCFFhKdDjJ4wdxdYJVhGXMP _4https://id.oclc.org/worldcat/ontology/hasWork |
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| 776 | 0 | 8 |
_iPrint version: _aChen, Ken. _tPerformance evaluation by simulation and analysis with applications to computer networks. _dLondon, [England] ; Hoboken, New Jersey : ISTE Limited : John Wiley & Sons, �2015 _hxxvii, 279 pages _z9781848217478 |
| 856 | 4 | 0 | _uhttps://onlinelibrary.wiley.com/doi/book/10.1002/9781119006190 |
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