

Beschreibung
This book provides an overview of the Internet of Things Network and Machine Learning and introduces Internet of Things architecture. It designs a new intelligent IoT network architecture and introduces different machine learning approaches to investigate solu...This book provides an overview of the Internet of Things Network and Machine Learning and introduces Internet of Things architecture. It designs a new intelligent IoT network architecture and introduces different machine learning approaches to investigate solutions. It discusses how machine learning can help network awareness and achieve network intelligent control. It also dicusses the emerging network techniques that can enable the development of intelligent IoT networks.
This book applies several intelligent approaches for efficient resource scheduling in networks. It discusses Mobile Edge Computing aided intelligent IoT and focuses mainly on the resource sharing and edge computation offloading problems in mobile edge networks. The blockchain-based IoT (which allows fairly and securely renting resources and establishing contracts) is discussed as well.
The Internet of Things refers to the billions of physical devices thatare now connected to and transfer data through the Internet without requiring human-to-human or human-to-computer interaction. According to Gartner's prediction, there will be more than 37 billion IoT connections in the future year of 2025. However, with large-scale IoT deployments, IoT networks are facing challenges in the aspects of scalability, privacy, and security. The ever-increasing complexity of the IoT makes effective monitoring, overall control, optimization, and auditing of the network difficult. Recently, artificial intelligence (AI) and machine learning (ML) approaches have emerged as a viable solution to address this challenge. Machine learning can automatically learn and optimize strategy directly from experience without following pre-defined rules. Therefore, it is promising to apply machine learning in IoT network control and management to leverage powerful machine learning adaptive abilities for higher network performance.
This book targets researchers working in the Internet of Things networks as well as graduate students and undergraduate students focused on this field. Industry managers, and government research agencies in the fields of the IoT networks will also want to purchase this book.
Presents an overview of Internet of Things Network and Machine Learning as well as emerging network technologies New intelligent Internet of Things network architecture introduces and applies machine learning interactions Illustrates how emerging network technologies (e.g., Mobile Edge Computing, Blockchain, and Programmable Network)
Autorentext
Haipeng Yao (IET Fellow) is a Professor in Beijing University of Posts and Telecommunications. Haipeng Yao received his Ph.D. in the Department of Telecommunication Engineering at University of Beijing University of Posts and Telecommunications in 2011. His research interests include future network architecture, network artificial intelligence, networking, space-terrestrial integrated network, network resource allocation and dedicated networks. He has published more than 200 papers in prestigious peer-reviewed journals and conferences. He won the IEEE ICC 2022 Best Paper Award, IEEE IWCMC 2019, 2021 Best Paper Award, IEEE ICCC 2020 Best Paper Award, IEEE HotICN 2020 Best Student Paper Award, authorized more than 100 national invention patents. He is a fellow of IET, a senior member of IEEE. Dr. Yao has served as an Associate Editor of IEEE Transactions on Mobile Computing, IEEE Transactions on Sustainable Computing, IEEE Network, IEEE ACCESS, and a Guest Editor of IEEE OPEN JOURNAL OF THE COMPUTER SOCIETY and Chain Communication. He has also served as a member of the technical program committee as well as the Symposium Chair for a number of international conferences, including IEEE IWCMC 2019 Symposium Chair, IEEE TrustCom 2021 Symposium Chair and an ACM TUR-C SIGSAC2020 Publication Chair. Tianle Mai received a Ph.D. degree in the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing. His research interests include unmanned swarm networks, future network architecture, network artificial intelligence, multi-agent system, space-terrestrial integrated network, network resource allocation and dedicated networks. He has published more than 40 papers in prestigious peer-reviewed journals and conferences. He won the IEEE ICC 2022 Best Paper Award, IEEE IWCMC 2021 Best Paper Award, IEEE ICCC 2020 Best Paper Award, IEEE HotICN 2020 Best Student Paper Award.
Inhalt
Introduction.- Intelligent Internet of Things Networking Architecture.- Intelligent IoT Network Awareness.- Intelligent Traffic Control.- Intelligent Resource Scheduling.- Mobile Edge Computing Enabled Intelligent IoT.- Blockchain Enabled Intelligent IoT.- Conclusions and Future Challenges.
