Название: Swarm Intelligence: Theory and Applications in Fog Computing, Beyond 5G Networks, and Information Security
Автор: V. Dinesh Reddy, Muzakkir Hussain, Priyanka Singh
Издательство: CRC Press
Год: 2025
Страниц: 259
Язык: английский
Формат: pdf (true), epub
Размер: 17.9 MB

This book offers a comprehensive overview of the theory and practical applications of swarm intelligence in fog computing, beyond 5G networks, and information security. The introduction section provides a background on swarm intelligence and its applications in real-world scenarios. The subsequent chapters focus on the practical applications of swarm intelligence in fog-edge computing, beyond 5G networks, and information security. The book explores various techniques such as computation offloading, task scheduling, resource allocation, spectrum management, radio resource management, wireless caching, joint resource optimization, energy management, path planning, UAV placement, and intelligent routing. Additionally, the book discusses the applications of swarm intelligence in optimizing parameters for information transmission, data encryption, and secure transmission in edge networks, multi-cloud systems, and 6G networks. The book is suitable for researchers, academics, and professionals interested in swarm intelligence and its applications in fog computing, beyond 5G networks, and information security. The book concludes by summarizing the key takeaways from each chapter and highlighting future research directions in these areas.

Fog computing, known for its architecture brings computation closer to the source of data. By integrating swarm intelligence into this framework we have the potential to revolutionize the efficiency and adaptability of edge computing systems. Moving forward the next chapter examines how swarm intelligence can be applied within the context of Internet of Things (IoT) and Edge Computing. As IoT continues to expand there is an increasing need for adaptable systems. The combination of swarm intelligence with edge computing offers solutions to enhance scalability, reliability and autonomy among interconnected devices. The third chapter introduces a metaheuristic based approach for optimizing the deployment of applications, on fog computing platforms. It is essential to conduct this investigation to ensure utilization of the fog environment maximizing resource allocation and enhancing the performance of the system. The intricate interplay of algorithms holds the potential to navigate the intricacies of deploying applications providing a roadmap, for the development of IoT systems based on fog computing.

The fourth chapter takes us into the world of wireless powered UAV IoT networks, where swarm intelligence is utilized for dynamic task allocation. This innovative approach not only helps optimize energy usage but also improves the efficiency of these networks demonstrating the transformative potential of swarm algorithms, in real life applications. The fifth chapter focuses on disaster management. It conducts a survey on the utilization of UAV swarms in search and rescue operations. By incorporating swarm intelligence into vehicles their capabilities are enhanced, making them invaluable tools in critical situations. This chapter showcases advancements but it also highlights the humanitarian aspect of swarm intelligence in responding to disasters.

Exploring the intersection between machine learning, deep learning and swarm algorithms the sixth chapter examines how these fields work together. As artificial intelligence continues to advance combining learning methods with swarm intelligence introduces approaches to problem solving, pattern recognition and decision making. Moving beyond networks the seventh chapter delves into the complexities surrounding privacy in swarm embedded systems. Specifically focusing on 5G networks this article explores topics such, as data anonymization, secure data transportation and user consent. The discussion goes beyond considerations by emphasizing dimensions and stressing the importance of responsible and secure implementation of swarm intelligence in eighth chapter.




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