AI-based advanced optimization techniques for edge computing / edited by Mohit Kumar, Gautam Srivastava, Ashutosh Kumar Singh and Kalka Dubey.

Includes bibliographical references and index.

Navigating next-generation network architecture : unleashing the power of SDN, NFV, NS, and AI convergence / Monika Dubey, Snehlata, Ashutosh Kumar Singh, Richa Mishra and Mohit Kumar -- OctoEdge : an octopus-inspired adaptive edge computing architecture / Sashi Tarun -- Development of optimized machine learning oriented models / Ratnesh Kumar Dubey, Dilip Kumar Choubey and Shubha Mishra -- Leveraging multimodal data and deep learning for enhanced stock market prediction / Pinky Gangwani and Vikas Panthi -- Context dependent sentiments analysis using machine learning / Mahima Shanker Pandey, Bihari Nandan Pandey, Abhishek Singh, Ashish Kumar Mishra and Brijesh Pandey -- Thyroid cancer prediction using optimizations / Swati Sharma, Vijay Kumar Sharma, Punit Mittal, Pradeep Pant and Nitin Rakesh -- An LSTM-oriented approach for next word prediction using deep learning / Nidhi Shukla, Ashutosh Kumar Singh, Vijay Kumar Dwivedi, Pallavi Shukla, Jeetesh Srivastava and Vivek Srivastava -- Churn prediction in social networks using modified BiLSTM-CNN model / Himanshu Rai and Jyoti Kesarwani -- Fog computing security concerns in healthcare using IoT and blockchain / Ruchi Mittal, Shikha Gupta and Shefali Arora -- Smart agriculture revolution : Cloud and IoT-based solutions for sustainable crop management and precision farming / Shrawan Kumar Sharma -- Greedy particle swarm optimization approach using leaky ReLU function for minimum spanning tree problem / Ashish Kumar Singh and Anoj Kumar -- SDN deployed secure application design framework for IoT using game theory / Madhukrishna Priyadarsini and Padmalochan Bera -- Framework for PLM in Industry 4.0 based on industrial blockchain / Ali Zaheer Agha, Rajesh Kumar Shukla, Ratnesh Mishra and Ravi Shankar Shukla -- Machine learning enabled smart agriculture classification technique for edge devices using remote sensing platform / Priyanka Gupta, Suraj Kumar Singh, Neetish Kumar and Bhavna Thakur -- A lightweight intelligent detection approach for interest flooding attack / Naveen Kumar, Brijendra Pratap Singh and Rohit -- An internet of vehicles model architecture with seven layers / Sujata Negi Thakur, Manisha Koranga, Sandeep Abhishek, Richa Pandey and Mayurika Joshi.

"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. 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."-- Provided by publisher.

Mohit Kumar, PhD, is an assistant professor in the Department of Information Technology at Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, India. He has published more than 60 research articles in reputed international journals and conferences and served as a session chair and keynote speaker for many international conferences and webinars in India. His research interests include cloud computing, soft computing, fog and edge computing, optimization algorithms, artificial Intelligence, and Internet of Things. Gautam Srivastava, PhD, is a professor at Brandon University, Manitoba, Canada with over eight years of academic experience. He has published more than 150 papers in various international journals and conferences and serves as an editor for several international journals. In addition to his written work, he has delivered guest lectures in Taiwan and the Czech Republic. His research interests include data mining, big data, cloud computing, Internet of Things, and cryptography. Ashutosh Kumar Singh, PhD, is an assistant professor in the Department of Computer Science and Engineering, United College of Engineering and Research Allahabad, India. He has published over 25 papers in reputed international journals and conferences and is a reviewer for various reputed journals, conferences, and books. His research interests include network optimization, software-defined networking, machine learning, Internet of Things, and edge computing. Kalka Dubey, PhD, is an assistant professor in the Department of Computer Science and Engineering, Rajiv Gandhi Institute of Petroleum Technology, Amethi, India. He has published more than 20 articles in international journals and conferences. His research interests include task scheduling, virtual machine placement and allocation in cloud-based systems, quantification and monitoring of security metrics, soft computing, and enforcing security in cloud environments.

Description based on online resource; title from digital title page (Wiley Online Library, viewed February 3, 2026).