LEADER 05440nam 2200673 450 001 9910787437203321 005 20230120002258.0 010 $a0-12-801743-0 010 $a0-12-801538-1 035 $a(CKB)3710000000354023 035 $a(EBL)1956673 035 $a(SSID)ssj0001466740 035 $a(PQKBManifestationID)11789409 035 $a(PQKBTitleCode)TC0001466740 035 $a(PQKBWorkID)11504546 035 $a(PQKB)10312142 035 $a(Au-PeEL)EBL1956673 035 $a(CaPaEBR)ebr11020384 035 $a(CaONFJC)MIL732174 035 $a(OCoLC)905866095 035 $a(CaSebORM)9780128015384 035 $a(MiAaPQ)EBC1956673 035 $a(EXLCZ)993710000000354023 100 $a20150228h20152015 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aBio-inspired computation in telecommunications /$fedited by Xin-She Yang, Su Fong Chien, Tiew On Ting 205 $aFirst edition. 210 1$aWaltham, Massachusetts :$cMorgan Kaufmann,$d2015. 210 4$dİ2015 215 $a1 online resource (349 p.) 300 $aDescription based upon print version of record. 311 $a1-336-00892-X 320 $aIncludes bibliographical references and index. 327 $aFront Cover; Bio-Inspired Computation in Telecommunications; Copyright ; Contents ; Preface ; List of Contributors ; Chapter 1: Bio-Inspired Computation and Optimization: An Overview; 1.1. Introduction; 1.2. Telecommunications and optimization; 1.3. Key challenges in optimization; 1.3.1. Infinite Monkey Theorem and Heuristicity; 1.3.2. Efficiency of an Algorithm; 1.3.3. How to Choose Algorithms; 1.3.4. Time Constraints; 1.4. Bio-inspired optimization algorithms; 1.4.1. SI-Based Algorithms; 1.4.1.1. Ant and bee algorithms; 1.4.1.2. Bat algorithm; 1.4.1.3. Particle swarm optimization 327 $a1.4.1.4. Firefly algorithm1.4.1.5. Cuckoo search; 1.4.2. Non-SI-Based Algorithms; 1.4.2.1. Simulated annealing; 1.4.2.2. Genetic algorithms; 1.4.2.3. Differential evolution; 1.4.2.4. Harmony search; 1.4.3. Other Algorithms; 1.5. Artificial neural networks; 1.5.1. Basic Idea; 1.5.2. Neural Networks; 1.5.3. Back Propagation Algorithm; 1.6. Support vector machine; 1.6.1. Linear SVM; 1.6.2. Kernel Tricks and Nonlinear SVM; 1.7. Conclusions; References; Chapter 2: Bio-Inspired Approaches in Telecommunications; 2.1. Introduction; 2.2. Design problems in telecommunications; 2.3. Green communications 327 $a2.3.1. Energy Consumption in Wireless Communications2.3.2. Metrics for Energy Efficiency; 2.3.3. Radio Resource Management; 2.3.4. Strategic Network Deployment; 2.4. Orthogonal frequency division multiplexing; 2.4.1. OFDM Systems; 2.4.2. Three-Step Procedure for Timing and Frequency Synchronization; 2.5. OFDMA model considering energy efficiency and quality-of-service; 2.5.1. Mathematical Formulation; 2.5.2. Results; 2.6. Conclusions; References; Chapter 3: Firefly Algorithm in Telecommunications; 3.1. Introduction; 3.2. Firefly algorithm; 3.2.1. Algorithm Complexity 327 $a3.2.2. Variants of Firefly Algorithm3.3. Traffic Characterization; 3.3.1. Network Management Based on Flow Analysis and Traffic Characterization; 3.3.2. Firefly Harmonic Clustering Algorithm; 3.3.3. Results; 3.4. Applications in wireless cooperative networks; 3.4.1. Related Work; 3.4.2. System Model and Problem Statement; 3.4.2.1. Energy and spectral efficiencies; 3.4.2.2. Problem statement; 3.4.3. Dinkelbach Method; 3.4.4. Firefly Algorithm; 3.4.5. Simulations and Numerical Results; 3.5. Concluding remarks; 3.5.1. FA in Traffic Characterization; 3.5.2. FA in Cooperative Networks; References 327 $aChapter 4: A Survey of Intrusion Detection Systems Using Evolutionary Computation4.1. Introduction; 4.2. Intrusion detection systems; 4.2.1. IDS Components; 4.2.2. Research Areas and Challenges in Intrusion Detection; 4.3. The method: evolutionary computation; 4.4. Evolutionary computation applications on intrusion detection; 4.4.1. Foundations; 4.4.2. Data Collection; 4.4.3. Detection Techniques and Response; 4.4.3.1. Intrusion detection on conventional networks; 4.4.3.2. Intrusion detection on wireless and resource-constrained networks; 4.4.4. IDS Architecture; 4.4.5. IDS Security 327 $a4.4.6. Testing and Evaluation 330 $a Bio-inspired computation, especially those based on swarm intelligence, has become increasingly popular in the last decade. Bio-Inspired Computation in Telecommunications reviews the latest developments in bio-inspired computation from both theory and application as they relate to telecommunications and image processing, providing a complete resource that analyzes and discusses the latest and future trends in research directions. Written by recognized experts, this is a must-have guide for researchers, telecommunication engineers, computer scientists and PhD students. 606 $aTelecommunication 606 $aBiologically-inspired computing 615 0$aTelecommunication. 615 0$aBiologically-inspired computing. 676 $a621.382 702 $aYang$b Xin-She 702 $aChien$b Su Fong 702 $aTing$b Tiew On 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910787437203321 996 $aBio-inspired computation in telecommunications$93743937 997 $aUNINA