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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.
5G technology along with a software- defined network (SDN) provides better data transmission mechanisms. SDN provides many benefits including reduced costs, ease of implementation and management, better scalability, availability, flexibility and granular traffic control, etc. SDN integrated within the edge- cloud interplay enhances QoS for complex IoT- driven applications. But various challenges remain, such as lack of security, energy management, controller placement management, and distribution strategies. This book covers cutting- edge methodologies, key technologies, use cases, review documents, and innovative use of SDNs for the interaction between edge and cloud in next- generation IoT infrastructures.
Chapter 1 discusses the detailed SDN- based IoT architecture with edge computing which offers a successful and robust environment for dealing with billions of devices in a meaningful and secure manner. A critical view of current trends in managing IoT devices and the various challenges related to privacy and security issues are highlighted. Further, the advantages of SDN- based IoT implementation are discussed, with conclusive evidence from real- time applications. Chapter 2 provides a brief overview of the evolution, capabilities, and applications of cloud- edge concepts, examining issues and challenges, along with use cases, real- time applications and future research trends. IoT edge devices generate a remarkable volume of raw data, leading to the evolution of accurate design models and many other smart applications in place of the network edge.
Edge computing (EC) along with software- defined network (SDN) and artificial intelligence (AI) has helped to resolve various problems including security challenges, resource allocation, task offloading, improving decision making, etc. SDN simplifies the complexity of IoT networks and AI helps with data privacy. Chapter 3 provides an insight into SDN-aided EC, AI- enabled IoT computing, and how technologies such as these have proved beneficial for the development of IoT devices and smart cities...
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.
SDN-Based IoT with Edge Computing
Towards Cloud-Edge-of-Things: State of the Art, Challenges and Future Trends
SDN-Aided Edge Computing-Enabled AI for IoT and Smart Cities
An Overview of Software-Defined Internet of Vehicles
IoT Architecture and Research Issues in the Smart City Environment
Performance Evaluation Methods for SDN Controllers: A Comparative Analysis
A Scalable Software-Defined Edge Computing Model for Sustainable Smart City Internet of Things (IoT) Application
Deep Learning Models with SDN and IoT for Intelligent Healthcare
Applications of Machine Learning Techniques in SD-IoT Traffic Management