Название: Computational Intelligence Techniques for 5G Enabled IoT Networks
Автор: Mohit Kumar, Sukhpal Singh Gill, Vijay Kumar, Prabal Verma
Издательство: Springer
Год: 2025
Страниц: 263
Язык: английский
Формат: pdf (true)
Размер: 26.4 MB

This book explores emerging interdisciplinary themes and applications reflecting advancements in Computational Intelligence (CI) for IoT and 5G networks. It is divided into four sections

Section 1 introduces Computational Intelligence and Sustainability Solutions for Next-Gen IoT Networks. Section 2 covers Optimization and Resilience Strategies for 5G-Enabled IoT Networks. Section 3 delves Intelligent Resource Allocation and Service Optimization in 5G IoT Networks. Section 4 presents Case studies on Applied Computational Intelligence and 5G IoT Innovations for Industry 4.0.

The introduction of 5G technologies is poised to change how we connect, communicate, and collaborate globally. Offering unmatched speed, extremely low latency, and the ability to connect numerous devices, 5G isn’t merely an enhancement of mobile networks but serves as a transformative base for the upcoming generation of the Internet of Things (IoT). This integration of 5G and IoT is expected to spark a fresh wave of innovation across various sectors, including smart cities, health care, transportation, and more. Nevertheless, the intricacy and scope of 5G-supported IoT networks present considerable challenges that demand creative solutions to guarantee optimal performance, sustainability, and scalability.

To tackle these challenges, techniques from computational intelligence (CI)—such as Machine Learning, Deep Learning, evolutionary algorithms, and Swarm Intelligence—are emerging as crucial facilitators. These methodologies, which draw inspiration from the adaptive and self-organizing features of biological systems, provide effective tools to optimize IoT network operations in real-time, manage resources effectively, and improve system resilience. Moreover, with the increasing prevalence of connected devices, the ecological effects of extensive IoT networks are becoming increasingly significant. The rise in energy usage, network congestion, and the overall carbon emissions from these networks is pressing issues. In light of this, computational intelligence presents a solution for developing sustainable IoT networks by facilitating adaptive and energy-efficient resource management. In addition to that, computational intelligence can be utilized to reduce energy usage, enhance network infrastructure, and boost the overall sustainability of IoT systems that are enabled by 5G technology.

This comprehensive work is essential for researchers and professionals interested in leveraging CI, IoT, and 5G technologies across diverse applications.