LEADER 00946nam0-22003251i-450- 001 990003339570403321 005 20080610103351.0 010 $a2190335748 035 $a000333957 035 $aFED01000333957 035 $a(Aleph)000333957FED01 035 $a000333957 100 $a20030910d1992----km-y0itay50------ba 101 0 $afre 102 $aFR 105 $ay-------001yy 200 1 $a<>expansion - 2 copie$eactualité économique et faits de société dans la France d'aujourd'hui$fChristiane Muglioni 210 $aParis$cCLE international$d1992 215 $a143 p.$cill.$d27 cm 610 0 $aLingua francese Letture 676 $a448.6 700 1$aMuglioni,$bChristiane$0131110 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990003339570403321 952 $a448.6/1$b2327 a$fDECLI 952 $a448.6/2$b2327 b$fDECLI 959 $aDECLI 996 $aExpansion - 2 copie$9442522 997 $aUNINA LEADER 06462nam 2200649 450 001 9910139511003321 005 20221206171134.0 010 $a1-282-49132-6 010 $a9786612491320 010 $a0-470-51521-X 010 $a0-470-51520-1 024 7 $a10.1002/9780470515211 035 $a(CKB)2550000000006554 035 $a(EBL)480422 035 $a(SSID)ssj0000340818 035 $a(PQKBManifestationID)11265603 035 $a(PQKBTitleCode)TC0000340818 035 $a(PQKBWorkID)10387093 035 $a(PQKB)11002803 035 $a(MiAaPQ)EBC480422 035 $a(CaBNVSL)mat08040181 035 $a(IDAMS)0b00006485f0e68f 035 $a(IEEE)8040181 035 $a(PPN)262085623 035 $a(OCoLC)587063572 035 $a(EXLCZ)992550000000006554 100 $a20171024d2008 uy 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aNetwork modeling and simulation $ea practical perspective /$fMohsen Guizani ... [et al.] 210 1$aChichester, West Sussex, U.K. :$cWiley,$d2010. 210 2$a[Piscataqay, New Jersey] :$cIEEE Xplore,$d[2010] 215 $a1 online resource (300 p.) 300 $aDescription based upon print version of record. 311 $a0-470-03587-0 320 $aIncludes bibliographical references and index. 327 $aPreface -- Acknowledgements -- 1 Basic Concepts and Techniques -- 1.1 Why Is Simulation Important? -- 1.2 What Is a Model? -- 1.3 Performance Evaluation Techniques -- 1.4 Development of Systems Simulation -- 1.5 Summary -- Recommended Reading -- 2 Designing and Implementing a Discrete-Event Simulation Framework -- 2.1 The Scheduler -- 2.2 The Simulation Entities -- 2.3 The Events -- 2.4 Tutorial 1: Hello World -- 2.5 Tutorial 2: Two-Node Hello Protocol -- 2.6 Tutorial 3: Two-Node Hello through a Link -- 2.7 Tutorial 4: Two-Node Hello through a Lossy Link -- 2.8 Summary -- Recommended Reading -- 3 Honeypot Communities: A Case Study with the Discrete-Event Simulation Framework -- 3.1 Background -- 3.2 System Architecture -- 3.3 Simulation Modeling -- 3.4 Simulation Execution -- 3.5 Output Analysis -- 3.6 Summary -- Recommended Reading -- 4 Monte Carlo Simulation -- 4.1 Characteristics of Monte Carlo Simulations -- 4.2 The Monte Carlo Algorithm -- 4.3 Merits and Drawbacks -- 4.4 Monte Carlo Simulation for the Electric Car Charging Station -- 4.5 Summary -- Recommended Reading -- 5 Network Modeling -- 5.1 Simulation of Networks -- 5.2 The Network Modeling and Simulation Process -- 5.3 Developing Models -- 5.4 Network Simulation Packages -- 5.5 OPNET: A Network Simulation Package -- 5.6 Summary -- Recommended Reading -- 6 Designing and Implementing CASiNO: A Network Simulation Framework -- 6.1 Overview -- 6.2 Conduits -- 6.3 Visitors -- 6.4 The Conduit Repository -- 6.5 Behaviors and Actors -- 6.6 Tutorial 1: Terminals -- 6.7 Tutorial 2: States -- 6.8 Tutorial 3: Making Visitors -- 6.9 Tutorial 4: Muxes -- 6.10 Tutorial 5: Factories -- 6.11 Summary -- Recommended Reading -- 7 Statistical Distributions and Random Number Generation -- 7.1 Introduction to Statistical Distributions -- 7.2 Discrete Distributions -- 7.3 Continuous Distributions -- 7.4 Augmenting CASiNO with Random Variate Generators -- 7.5 Random Number Generation -- 7.6 Frequency and Correlation Tests -- 7.7 Random Variate Generation. 327 $a7.8 Summary -- Recommended Reading -- 8 Network Simulation Elements: A Case Study Using CASiNO -- 8.1 Making a Poisson Source of Packets -- 8.2 Making a Protocol for Packet Processing -- 8.3 Bounding Protocol Resources -- 8.4 Making a Round-Robin (De)multiplexer -- 8.5 Dynamically Instantiating Protocols -- 8.6 Putting It All Together -- 8.7 Summary -- 9 Queuing Theory -- 9.1 Introduction to Stochastic Processes -- 9.2 Discrete-Time Markov Chains -- 9.3 Continuous-Time Markov Chains -- 9.4 Basic Properties of Markov Chains -- 9.5 Chapman / Kolmogorov Equation -- 9.6 Birth / Death Process -- 9.7 Little's Theorem -- 9.8 Delay on a Link -- 9.9 Standard Queuing Notation -- 9.10 The M/M/1 Queue -- 9.11 The M/M/m Queue -- 9.12 The M/M/1/b Queue -- 9.13 The M/M/m/m Queue -- 9.14 Summary -- Recommended Reading -- 10 Input Modeling and Output Analysis -- 10.1 Data Collection -- 10.2 Identifying the Distribution -- 10.3 Estimation of Parameters for Univariate Distributions -- 10.4 Goodness-of-Fit Tests -- 10.5 Multivariate Distributions -- 10.6 Selecting Distributions without Data -- 10.7 Output Analysis -- 10.8 Summary -- Recommended Reading -- 11 Modeling Network Traffic -- 11.1 Introduction -- 11.2 Network Traffic Models -- 11.3 Traffic Models for Mobile Networks -- 11.4 Global Optimization Techniques -- 11.5 Particle Swarm Optimization -- 11.6 Optimization in Mathematics -- 11.7 Summary -- Recommended Reading -- Index. 330 $aNetwork Modeling and Simulation is a practical guide to using modeling and simulation to solve real-life problems. The authors give a comprehensive exposition of the core concepts in modeling and simulation, and then systematically address the many practical considerations faced by developers in modeling complex large-scale systems. The authors provide examples from computer and telecommunication networks and use these to illustrate the process of mapping generic simulation concepts to domain-specific problems in different industries and disciplines. Key features: . Provides the tools and strategies needed to build simulation models from the ground up rather than providing solutions to specific problems.. Includes a new simulation tool, CASiNO built by the authors.. Examines the core concepts of systems simulation and modeling.. Presents code examples to illustrate the implementation process of commonly encountered simulation tasks.. Offers examples of industry-standard modeling methodology that can be applied in steps to tackle any modeling problem in practice. 606 $aSimulation methods 606 $aMathematical models 606 $aNetwork analysis (Planning)$xMathematics 615 0$aSimulation methods. 615 0$aMathematical models. 615 0$aNetwork analysis (Planning)$xMathematics. 676 $a003.346 701 $aGuizani$b Mohsen$0846524 801 0$bCaBNVSL 801 1$bCaBNVSL 801 2$bCaBNVSL 906 $aBOOK 912 $a9910139511003321 996 $aNetwork modeling and simulation$92231450 997 $aUNINA LEADER 01312nam 2200421 450 001 9910829846003321 005 20230411133413.0 010 $a1-119-87198-0 010 $a1-119-87197-2 035 $a(MiAaPQ)EBC7147270 035 $a(Au-PeEL)EBL7147270 035 $a(CKB)25483513000041 035 $a(EXLCZ)9925483513000041 100 $a20230411d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aAutonomous vehicles$hVolume 1 $eusing machine intelligence /$fedited by Romil Rawat 210 1$aHoboken, New Jersey :$cJohn Wiley & Sons, Incorporated,$d[2023] 210 4$d©2023 215 $a1 online resource (315 pages) 311 08$aPrint version: Rawat, Romil Using Machine Intelligence Newark : John Wiley & Sons, Incorporated,c2023 9781119871958 320 $aIncludes bibliographical references and index. 606 $aAutomated vehicles 606 $aMachine learning 615 0$aAutomated vehicles. 615 0$aMachine learning. 676 $a343.0946 702 $aRawat$b Romil 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910829846003321 996 $aAutonomous Vehicles$91937090 997 $aUNINA