Expected by: 01 February 2024
Enabling Technologies for Smart Fog Computing

Enabling Technologies for Smart Fog Computing

by Kuldeep Singh Kaswan, Jagjit Singh Dhatterwal, Vivek Jaglan, Balamurugan Balusamy, Kiran Sood, Thanh Thi Nguyen

Fog computing is a decentralized computing infrastructure in which computing resources are located between the data source and the cloud or any other data centers. The word "fog" refers to its cloud-like properties, which are closer to the "ground", using edge devices that carry out locally computation, storage and communication tasks. An additional benefit is that the processed data is likely to be needed by the same devices that generated the data. By processing locally rather than remotely, the latency between input and response are minimized. This technology has countless application domains such as industrial process control, smart cities, transportation, healthcare and agriculture.

In this book, all the important topics in fog computing systems are covered, including energy efficiency, quality of service (QoS) issues, reliability and fault tolerance, load balancing, and scheduling. Special attention is devoted to emerging trends and industry needs associated with utilizing mobile edge computing, internet of things (IoT), resource estimation as well as virtualization in the fog computing environment. Current research on automation, robotics, data privacy, security and trust in fog computing is explored in depth. The book also discusses emerging techniques including deep learning, mobile edge computing, smart grid and intelligent transportation systems beyond theoretical and foundational concepts for smart applications including real time traffic surveillance, interoperability of fog computing architecture and smart homes and smart cities.

Intended for an audience of researchers from academia and industry, as well as lecturers, engineers and advanced students, Enabling Technologies for Smart Fog Computing offers valuable insights for those with an interest in the field.

About the Author

Kuldeep Singh Kaswan is a professor in the School of Computing Science & Engineering, Galgotias University, Greater Noida, Uttar Pradesh, India. His research contributions focus on cloud and fog computing, data science, BCI and cyborgs. He is a member of CSTA, (USA), IAENG (Hong Kong), IACSIT (USA), ACM (USA), and IEEE. He is an author of several authored and edited books. He received his doctorate degree from Banasthali Vidyapith University, Rajasthan, India.

Jagjit Singh Dhatterwal is an associate professor in the Department of Artificial Intelligence & Data Science (AI&DS), Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India. His areas of interest include artificial intelligence and multi-agents technology. He is a member of CSTA (USA), IAENG (Hong Kong), IACSIT (USA,) and ACM (USA), and a life member of the Computer Society of India.

Vivek Jaglan is a professor and director at Amity School of Engineering and Technology, Amity University, Gwalior, India. His current research areas cover artificial intelligence, neural networks, fuzzy logic and IoT. He has presented and published 80+ papers in journals and conferences. He holds a doctorate degree from the Computer Science and Engineering Department, SGV University, Jaipur, India.

Balamurugan Balusamy is a professor at the School of Computing Science and Engineering, Galgotias University, India. His research focuses on blockchain and IoT. He has published 30 technology books and over 150 journal and conference papers and book chapters. He serves on the advisory committee for several start-ups and forums and does consultancy work for the industry on Industrial IoT. He has given over 175 talks at events and symposiums.

Kiran Sood is a professor at Chitkara Business School, Chitkara University, Punjab, India; an affiliate professor in the faculty of Economics Management and Accountancy at the University of Malta; and a postdoc researcher in the faculty of Applied Sciences at the University of Usak, Turkey. Her areas of research cover the fields of big data and finance. She serves as an editor for several refereed journals.

Thanh Thi Nguyen is an associate professor in the Department of Data Science & AI, Faculty of Information Technology at Monash University, Victoria, Australia. He was previously at Deakin University. His areas of expertise include artificial intelligence, deep learning, deep reinforcement learning, cyber security, IoT, and data science. He received an Australia-India Strategic Research Fund Early- and Mid-Career Fellowship Award from the Australian Academy of Science in 2020.

Item Subjects:
Computing and Networks

Publication Year: 2024

Pages: 350

ISBN-13: 978-1-83953-749-3

Format: HBK

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