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This covers challenges, opportunities, and open research directions for Cyber-Physical Systems (CPS). It focuses on the design and development of Machine Learning/Metaheuristics-enabled methods, and Blockchain for security, resource management, computation offloading, trust management, and others in edge, fog/cloud computing, IoT, & IoE.
List of contents
1. Delay-Aware Partial Computational Offloading and Resource Allocation in Fog-Enabled Cyber-Physical Systems 2. Enhancing the Security of Cryptographic Algorithms in Cloud-Based Cyber-Physical Systems (CCPS) 3. Containerized Deployment of Microservices in Cloud Computing 4. RSS-Based Smart Device Localization using Few-Shot Learning in IoT Networks 5. Data-Driven Risk Modelling of Cyber-Physical Systems 6. Automation of the Process of Analysis of Information Security Threats in Cyber-Physical Systems 7. IoT in Healthcare: Glucose Tracking System 8. Intelligent Application to Support Smart Farming Using Cloud Computing: Future Perspectives 9. Cybersecurity in Automous Vehicles 10. Use of Virtual Payment Hubs over Cryptocurrencies 11. Akaike's Information Criterion Algorithm for Online Cashback in Vietnam 12. Capacitated Vehicle Routing Problem Using Algebraic Harris Hawks Optimization Algorithm 13. Technology for Detecting Harmful Effects on the UAV Navigation and Communication System 14. Current and Future Trends of Intelligent Transport System Using AI in Rural Areas 15. Future Technology: Internet of Things (IoT) in Smart Society 5.0 16. IoT, Cloud Computing, and Sensing Technology for Smart Cities 17. Utilization of Artificial Intelligence in Electrical Engineering 18. Major Security Issues and Data Protection in Cloud Computing and IoT
About the author
Mohammad Sajid is Assistant Professor in the Department of Computer Science at Aligarh Muslim University, India. He has completed his Ph.D., M.Tech., and MCA degrees at the School of Computer and Systems Sciences, Jawaharlal Nehru University (JNU), New Delhi. His research interests include parallel and distributed computing, cloud computing, bio-inspired computation, and combinatorial optimization problems. He has published one patent and was awarded a research start-up grant in 2017 from University Grants Commission (UGC), India.
Anil Kumar Sagar is Professor in the Department of Computer Science and Engineering at Sharda University Greater Noida, India. He completed his B.E., M.Tech., Ph.D. in Computer Science. His research interests include mobile ad hoc networks and vehicular ad hoc networks, IoT, and artificial intelligence. He has received a Young Scientist Award for the year 2018-2019 from the Computer Society of India and the Best Faculty Award for the years 2006 and 2007 from SGI, Agra.
Jagendra Singh is Associate Professor in the School of Computer Science, Engineering and Technology, Bennett University, Greater Noida. He received his Ph.D. in Computer Science from Jawaharlal Nehru University, New Delhi. His areas of interest are natural language processing (information retrieval system, recommendation system, sentiment analysis) and machine learning (deep learning, neural network, and data analytics).
Osamah Ibrahim Khalaf is Senior Assistant Professor in Engineering and Telecommunications at Al-Nahrain University/College of Information Engineering. He holds 10 years of university-level teaching experience in computer science and network technology, holds patents, and has received several medals and awards due to his innovative work and research activities. He earned his Ph.D. in Computer Networks from the Faculty of Computer Systems and Software Engineering, University of Malaysia Pahang. He has overseas work experience at Binary University in Malaysia and University of Malaysia Pahang.
Mukesh Prasad is Senior Lecturer at the School of Computer Science in the Faculty of Engineering and IT at the University of Technology Sydney. His research interests include big data, computer vision, brain-computer interface, and evolutionary computation. He is also working in the field of image processing, data analytics, and edge computing. His research is backed by industry experience, specifically in Taiwan, where he was the principal engineer (2016-2017) at the Taiwan Semiconductor Manufacturing Company (TSMC). He received a Ph.D. from the Department of Computer Science at the National Chiao Tung University in Taiwan (2015).
