This book discusses the future possibilities of AI with cloud computing and edge computing. The main goal of this book is to conduct analyses, implementation and discussion of many tools (of artificial intelligence, machine learning and deep learning and cloud computing, fog computing, and edge computing including concepts of cyber security) for understanding integration of these technologies. With this book, readers can quickly get an overview of these emerging topics and get many ideas of the future of AI with cloud, edge, and in many other areas. Topics include machine and deep learning techniques for Internet of Things based cloud systems; security, privacy and trust issues in AI based cloud and IoT based cloud systems; AI for smart data storage in cloud-based IoT; blockchain based solutions for AI based cloud and IoT based cloud systems.This book is relevent to researchers, academics, students, and professionals.

Table of Contents

1. An Optimization View to the Design of Edge Computing Infrastructures for loT Applications
2. AIOps: A Multivocal Literature Review
3. Deep Learning-Based Facial Recognition on Hybrid Architecture for Financial Services
4. Classification of Swine Disease Using K-Nearest Neighbor Algorithm on Cloud-Based Framework
5. Privacy and Trust Models for Cloud-Based EH Rs Using Multilevel Cryptography and Artificial Intelligence
6. Utilizing an Agent-Based Auction Protocol for Resource Allocation and Load Balancing in Grid Computing
7. Optimization Model of Smartphone and Smart Watch Based on Multi Level of Elitism (OMSPW-MLE)
8. K-Nearest Neighbour Algorithm for Classification of loT-Based Edge Computing Device
9. Big Data Analytics of loT-Based Cloud System Framework: Smart Healthcare Monitoring Systems
10. Genetic Algorithm-Based Pseudo Random Number Generation for Cloud Security
11. Anomaly Detection in loT Using Machine Learning
12. System Level Knowledge Representation for Edge Intelligence
13. Al-Based Enhanced Time Cost-Effective Cloud Workflow Scheduling
14. AI-JasCon: An Artificial Intelligent Containerization System for Bayesian Fraud Determination in Complex Networks
15. Performance Improvement of Intrusion Detection System for Detecting Attacks on Internet of Things and Edge of Things

About the Authors

Sanjay Misra is a professor at Ostfold University College(HIOF), Halden Norway. Before coming to HIOF, he was a professor in Covenant University (400–500 ranked by THE(2019)) Nigeria for 9 years. He received his PhD. in Inf. & Know. Engg (Software Engg) from the University of Alcala, Spain and M.Tech. (Software Engg) from MLN National Institute of Tech, India. As per SciVal (SCOPUS – Elsevier) analysis (on 01.09.2021), he is the most productive researcher (Number 1) https://t.co/fBYnVxbmiL in Nigeria since 2017 (in all disciplines), in comp science no 1 in the country & no 2 in the whole of Africa. Total more than 500 articles (SCOPUS/WoS) with 500 coauthors worldwide (-110 JCR/SCIE) in the core & appl. area of Soft Engg, Web engineering, Health Informatics, Cybersecurity, Intelligent systems, AI, etc. He got several awards for outstanding publications (2014 IET Software Premium Award(UK)), and from TUBITAK-Turkish Higher Education and Atilim University). He has delivered more than 100 keynote/invited talks/public lectures in reputed conferences and institutes (traveled to more than 60 countries). He is one of the editors of 58 LNCSs, 4 LNEEs, 1 LNNSs, 3 CCISs & 10 IEEE proceedings and 6 books, and editor in chief of IT Personnel and Project Management and Int J of Human Capital & Inf Technology Professionals – IGI Global and editor in various SCIE journals.

Amit Kumar Tyagi is Assistant Professor (Senior Grade), and Senior Researcher at Vellore Institute of Technology (VIT), Chennai Campus, India. His current research focuses on Machine Learning with Big data, Blockchain Technology, Data Science, Cyber Physical Systems, Smart & Secure Computing and Privacy. He has contributed to several projects such as “AARIN” and “P3-Block” to address some of the open issues related to the privacy breaches in Vehicular Applications (such as Parking) and Medical Cyber Physical Systems. He received his Ph.D. Degree from Pondicherry Central University, India. He is a member of the IEEE.Vincenzo Piuri has received his Ph.D. in computer engineering at Politecnico di Milano, Italy (1989). He is Full Professor in computer engineering at the Università degli Studi di Milano, Italy (since 2000). He has been Associate Professor at Politecnico di Milano, Italy and Visiting Professor at the University of Texas at Austin and at George Mason University, USA.

His main research interests are: artificial intelligence, computational intelligence, intelligent systems, machine learning, pattern analysis and recognition, signal and image processing, biometrics, intelligent measurement systems, industrial applications, digital processing architectures, fault tolerance, dependability, and cloud computing infrastructures. Original results have been published in more than 400 papers in international journals, proceedings of international conferences, books, and book chapters. He is Fellow of the IEEE, Distinguished Scientist of ACM, and Senior Member of INNS. He is President of the IEEE Systems Council (2020-21), and has been IEEE Vice President for Technical Activities (2015), IEEE Director, President of the IEEE Computational Intelligence Society, Vice President for Education of the IEEE Biometrics Council, Vice President for Publications of the IEEE Instrumentation and Measurement Society and the IEEE Systems Council, and Vice President for Membership of the IEEE Computational Intelligence Society. He is Editor-in-Chief of the IEEE Systems Journal (2013-19), and Associate Editor of the IEEE Transactions on Cloud Computing, and has been Associate Editor of the IEEE Transactions on Computers, the IEEE Transactions on Neural Networks, the IEEE Transactions on Instrumentation and Measurement, and IEEE Access. He received the IEEE Instrumentation and Measurement Society Technical Award (2002) and the IEEE TAB Hall of Honor (2019). He is Honorary Professor at: Obuda University, Hungary; Guangdong University of Petrochemical Technology, China; Northeastern University, China; Muroran Institute of Technology, Japan; and the Amity University, India.

Lalit Garg is a Senior Lecturer in Computer Information Systems at the University of Malta, Malta and an honorary lecturer at the University of Liverpool, UK. He has also worked as a researcher at the Nanyang Technological University, Singapore and Ulster University, UK. His supervision experience includes more than 190 Masters' dissertations and four PhD thesis. He has edited two books and published over 100 papers in refereed high impact journals, conferences and books, and some of his articles awarded best paper awards. He has delivered more than twenty keynote speeches in different countries, organised/chaired/co-chaired a similar number of international conferences. He was awarded research studentship in Healthcare Modelling to carry out his PhD research studies in the faculty of computing and engineering at Ulster University, UK. His doctoral research was nominated for the Operational Research Society Doctoral Prize "Most Distinguished Body of Research leading to the Award of a Doctorate in the field of OR". He has also consulted numerous public and private organisations for their information system implementations. His research interests are missing data handling, machine learning, data mining, mathematical and stochastic modelling, and operational research, and their applications, especially in the healthcare domain.