01869nam a22002657a 4500 20260724122826.0 260724s2025 |||||||| |||| 00| 0 eng d 9781394287031 PK-LaUMT 006.31 AIB- AI-based advanced optimization techniques for edge computing / edited by Mohit Kumar . . . [et al.] Hoboken : John Wiley & Sons, Inc., 2025 xvii, 460 p. Advances in learning analytics for intelligent cloud-IoT systems Includes bibliographical references and index. The 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. Eng Edge computing-Technological innovations 14151 Machine learning Mohit Kumar 14152 Srivastava, Gautam 14153 Singh, Ashutosh Kumar 14154 Dubey, Kalka 14155 BK 141635 141635 0 0 0 0 01 01 2026-07-24 0 006.31 AIB- 153529 2026-07-24 12:28:36 2026-07-24 BK