Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation
- 6h 14m
- Danda B. Rawat, Jitendra Kumar Samriya, Lalit K. Awasthi, Mohit Kumar, Valentina Emilia Balas
- John Wiley & Sons (US)
- 2023
CONVERGENCE of CLOUD with AI for BIG DATA ANALYTICS
This book covers the foundations and applications of cloud computing, AI, and Big Data and analyses their convergence for improved development and services.
The 17 chapters of the book masterfully and comprehensively cover the intertwining concepts of artificial intelligence, cloud computing, and big data, all of which have recently emerged as the next-generation paradigms. There has been rigorous growth in their applications and the hybrid blend of AI Cloud and IoT (Ambient-intelligence technology) also relies on input from wireless devices. Despite the multitude of applications and advancements, there are still some limitations and challenges to overcome, such as security, latency, energy consumption, service allocation, healthcare services, network lifetime, etc. Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation details all these technologies and how they are related to state-of-the-art applications, and provides a comprehensive overview for readers interested in advanced technologies, identifying the challenges, proposed solutions, as well as how to enhance the framework.
Audience
Researchers and post-graduate students in computing as well as engineers and practitioners in software engineering, electrical engineers, data analysts, and cyber security professionals.
About the Author
Danda B Rawat, PhD, is a Full Professor in the Department of Electrical Engineering & Computer Science (EECS), Founder and Director of the Howard University Data Science and Cybersecurity Center, Director of DoD Center of Excellence in Artificial Intelligence & Machine Learning, Director of Cyber-security and Wireless Networking Innovations Research Lab, Graduate Program Director of Howard CS Graduate Programs, and Director of Graduate Cybersecurity Certificate Program at Howard University, Washington, DC, USA. Dr. Rawat has published more than 250 scientific/technical articles and 11 books.
Lalit K Awasthi, PhD, is the Director of Dr. B. R. Ambedkar National Institute of Technology Jalandhar, India). He received his PhD degree from the Indian Institute of Technology Roorkee in computer science and engineering. He has published more than 150 research papers in various journals and conferences of international repute and guided many PhDs in these areas.
Valentina E Ballas, PhD, is a Full Professor in the Department of Automatics and Applied Software at the Faculty of Engineering, “Aurel Vlaicu” University of Arad, Romania. Dr. Ballas is the author of more than 280 research papers in refereed journals and international conferences. She is the Editor-in-Chief of International Journal of Advanced Intelligence Paradigms and International Journal of Computational Systems Engineering.
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 received his PhD degree from the Indian Institute of Technology Roorkee in the field of cloud computing in 2018. His research topics cover the areas of cloud computing, fog computing, edge computing, Internet of Things, soft computing, and blockchain. He has published more than 25 research articles in international journals and conferences.
Jitendra Kumar Samriya, PhD, has a faculty position in the Department of Information Technology, Dr. B.R. Ambedkar National Institute of Technology, Jalandhar. His research interest is cloud computing, artificial intelligence, and multi-objective evolutionary optimization techniques. He has published 15 research articles in international journals and has published five Indian and international patents.
In this Book
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Integration of Artificial Intelligence, Big Data, and Cloud Computing with Internet of Things
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Cloud Computing and Virtualization
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Time and Cost-Effective Multi-Objective Scheduling Technique for Cloud Computing Environment
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Cloud-Based Architecture for Effective Surveillance and Diagnosis of COVID-19
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Smart Agriculture Applications Using Cloud and IoT
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Applications of Federated Learning in Computing Technologies
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Analyzing the Application of Edge Computing in Smart Healthcare
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Fog-IoT Assistance-Based Smart Agriculture Application
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Internet of Things in the Global Impacts of COVID-19—A Systematic Study
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An Efficient Solar Energy Management Using IoT-Enabled Arduino-Based MPPT Techniques
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Cloud Computing and Virtualization
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APP-Based Agriculture Information System for Rural Farmers in India
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SSAMH – A Systematic Survey on AI-Enabled Cyber Physical Systems in Healthcare
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ANN-Aware Methanol Detection Approach with CuO-Doped SnO2 in Gas Sensor
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Detecting Heart Arrhythmias using Deep Learning Algorithms
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Artificial Intelligence Approach for Signature Detection
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Comparison of Various Classification Models Using Machine Learning to Predict Mobile Phones Price Range
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