Software-Defined Networking for Future Internet Technology Concepts and Applications

Network infrastructures are growing rapidly to meet the needs of business, but the required repolicing and reconfiguration provide challenges that need to be addressed. The software-defined network (SDN) is the future generation of Internet technology that can help meet these challenges of network management.

This book includes quantitative research, case studies, conceptual papers, model papers, review papers, and theoretical backing on SDN. This book investigates areas where SDN can help other emerging technologies deliver more efficient services, such as IoT, industrial IoT, NFV, big data, blockchain, cloud computing, and edge computing. The book demonstrates the many benefits of SDNs, such as reduced costs, ease of deployment and management, better scalability, availability, flexibility and fine-grained control of traffic, and security.

The book demonstrates the many benefits of SDN, such as reduced costs, ease of deployment and management, better scalability, availability, flexibility and fine-grained control of traffic, and security.

Chapters in the volume address:

• Design considerations for security issues and detection methods
• State-of-the-art approaches for mitigating DDos attacks using SDN
• Big data using Apache Hadoop for processing and analyzing large amounts of data
• Different tools used for attack simulation
• Network policies and policy management approaches that are widely used in the context of SDN
• Dynamic flow tables, or static flow table management
• A new four-tiered architecture that includes cloud, SDN-controller, and fog computing
• Architecture for keeping computing resources available near the industrial IoT network through edge computing
• The impact of SDN as an innovative approach for smart city development
• More.

The book will be a valuable resource for SDN researchers as well as academicians, research scholars, and students in the related areas.

1. Security Issues in SDN 2. Distributed Denial of Service Attacks in SDN Context 3. Policy Management in Software-Defined Networks 4. Flow Table Scalability in Software-Defined Networking: A Brief Overview 5. Micro-Service Provisioning in the Multi-Tier SDN-Fog Architecture for IoT Applications 6. Blockchain-Supported Cloud Architecture for Software-Defined Industrial IoT 7. DDoS Attack Detection in Software-Defined IoT: A Big Picture 8. SDN-Enabled Fog Computing Architecture 9. Software-Defined Industrial IoT for Smart City Applications 10. Software-Defined Network and Network Function Virtualization: A Comparative Study

Kshira Sagar Sahoo, PhD, is Assistant Professor in the Department of Computer Science and Engineering at SRM University, Amaravati, AP, India. He has authored papers in several reputed journals, including those published by IEEE Transactions, Wiley, Springer, and Elsevier, as well as in conference proceedings. His research interests include future generation network infrastructure such as software-defined networks, edge computing, IoT, etc.

Bibhudatta Sahoo, PhD, is Associate Professor in the Department of Computer Science and Engineering, National Institute of Technology, Rourkela, India. He has over 25 years of teaching experience in computer science and engineering. He has authored papers in journals and in conference proceedings. His interests include data structures and algorithm design, parallel and distributed systems, computational machines, algorithms for VLSI design, performance evaluation methods and modeling techniques, distributed computing system, networking algorithms, and web engineering.

Brojo Kishore Mishra, PhD, is Professor in the Computer Science and Engineering Department at the Gandhi Institute of Engineering and Technology University, Gunupur, Odisha, India. He has published more than 40 research papers in journals and conferences, and seven book chapters. He has edited a book and is an editorial board member/associate editor/guest editor for various international journals. His research interests include data mining and big data analysis, machine learning, soft computing, and evolutionary computation.