LEADER 05262nam 22006013 450 001 9911020105703321 005 20260720211924.0 010 $a9781394287048 010 $a1394287046 010 $a9781394287062 010 $a1394287062 010 $a9781394287055 010 $a1394287054 010 $a1-394-28705-4 035 $a(CKB)38011657600041 035 $a(MiAaPQ)EBC31974309 035 $a(Au-PeEL)EBL31974309 035 $a(OCoLC)1509787695 035 $a(BIP)109703922 035 $a(BIP)109501465 035 $a(FI-CZ)9781394287048 035 $a(UkBuK)3370510 035 $a(EXLCZ)9938011657600041 100 $a20250328d2025 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAI-Based Advanced Optimization Techniques for Edge Computing 205 $a1st ed. 210 1$cWiley$d2025 215 $a1 online resource (481 pages) 225 0 $aAdvances in learning analytics for intelligenct cloud-IOT systems 311 08$a9781394287031 311 08$a1394287038 311 08$a1-394-28703-8 327 $tSeries Page$t1 Navigating Next-Generation Network Architecture: Unleashing the Power of SDN, NFV, NS, and AI Convergence$t2 OctoEdge: An Octopus-Inspired Adaptive Edge Computing Architecture$t3 Development of Optimized Machine Learning Oriented Models$t4 Leveraging Multimodal Data and Deep Learning for Enhanced Stock Market Prediction$t5 Context Dependent Sentiments Analysis Using Machine Learning$t6 Thyroid Cancer Prediction Using Optimizations$t7 An LSTM-Oriented Approach for Next Word Prediction Using Deep Learning$t8 Churn Prediction in Social Networks Using Modified BiLSTM-CNN Model$t9 Fog Computing Security Concerns in Healthcare Using IoT and Blockchain$t10 Smart Agriculture Revolution: Cloud and IoT-Based Solutions for Sustainable Crop Management and Precision Farming$t11 Greedy Particle Swarm Optimization Approach Using Leaky ReLU Function for Minimum Spanning Tree Problem$t12 SDN Deployed Secure Application Design Framework for IoT Using Game Theory$t13 Framework for PLM in Industry 4.0 Based on Industrial Blockchain$t14 Machine Learning Enabled Smart Agriculture Classification Technique for Edge Devices Using Remote Sensing Platform$t15 A Lightweight Intelligent Detection Approach for Interest Flooding Attack$t16 An Internet of Vehicles Model Architecture with Seven Layers$tEnd User License Agreement 330 $aThe book offers cutting-edge insights into AI-driven optimization algorithms and their crucial role in enhancing real-time applications within fog and Edge IoT networks and addresses current challenges and future opportunities in this rapidly evolving field. This book focuses on artificial intelligence-induced adaptive optimization algorithms in fog and Edge IoT networks. Artificial intelligence, fog, and edge computing, together with IoT, are the next generation of paradigms offering services to people to improve existing services for real-time applications. Over the past few years, there has been rigorous growth in AI-based optimization algorithms and Edge and IoT paradigms. However, despite several applications and advancements, there are still some limitations and challenges to address including security, adaptive, complex, and heterogeneous IoT networks, protocols, intelligent offloading decisions, latency, energy consumption, service allocation, and network lifetime. This volume aims to encourage industry professionals to initiate a set of architectural strategies to solve open research computation challenges. The authors achieve this by defining and exploring emerging trends in advanced optimization algorithms, AI techniques, and fog and Edge technologies for IoT applications. Solutions are also proposed to reduce the latency of real-time applications and improve other quality of service parameters using adaptive optimization algorithms in fog and Edge paradigms. The book provides information on the full potential of IoT-based intelligent computing paradigms for the development of suitable conceptual and technological solutions using adaptive optimization techniques when faced with challenges. Additionally, it presents in-depth discussions in emerging interdisciplinary themes and applications reflecting the advancements in optimization algorithms and their usage in computing paradigms. Audience Researchers, industrial engineers, and graduate/post-graduate students in software engineering, computer science, electronic and electrical engineering, data analysts, and security professionals working in the fields of intelligent computing paradigms and similar areas. 606 $aCOMPUTERS / Artificial Intelligence / General$2bisacsh 615 7$aCOMPUTERS / Artificial Intelligence / General 676 $a006.3 700 $aMohit$b Kumar$01886969 701 $aSrivastava$b Gautam$01802732 701 $aSingh$b Ashutosh Kumar$01785463 701 $aDubey$b Kalka$01837544 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911020105703321 996 $aAI-Based Advanced Optimization Techniques for Edge Computing$94526948 997 $aUNINA