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Full Description
SDN-Supported Edge-Cloud Interplay for Next Generation Internet of Things is an invaluable resource coveringa wide range of research directions in the field of edge-cloud computing, SDN, and IoT. The integration of SDN in edge-cloud interplay is a promising framework for enhancing the QoS for complex IoT-driven applications. The interplay between cloud and edge solves some of the major challenges that arise in traditional IoT architecture. This book is a starting point for those involved in this research domain and explores a range of significant issues including network congestion, traffic management, latency, QoS, scalability, security, and controller placement problems.
Features:
The book covers emerging trends, issues and solutions in the direction of Edge-cloud interplay
It highlights the research advances in on SDN, edge, and IoT architecture for smart cities, and software-defined internet of vehicles
It includes detailed discussion has made of performance evaluations of SDN controllers, scalable software-defined edge computing, and AI for edge computing
Applications areas include machine learning and deep learning in SDN-supported edge-cloud systems
Different use cases covered include smart health care, smart city, internet of drones, etc
This book is designed for scientific communities including graduate students, academicians, and industry professionals who are interested in exploring technologies related to the internet of things such as cloud, SDN, edge, internet of drones, etc.
Contents
1. SDN based IoT with Edge computing. 2. Towards Cloud-Edge-of-Things: State-of-the-Art, Challenges and Future Trends. 3. SDN-Aided Edge Computing Enabled AI for IOT and Smart Cities. 4. An Overview of Software-Defined Internet of Vehicles. 5. IoT Architecture and Research Issues in the Smart City Environment. 6. Performance Evaluation Methods for SDN Controllers: A Comparative Analysis. 7. A Scalable Software Defined Edge Computing Model for Sustainable Smart City Internet of Things (IoT) Application. 8. Deep Learning Models with SDN and IOT for Intelligent Healthcare. 9. Applications of Machine Learning Techniques in SD- IoT Traffic Management
