Software-Defined Networking and Artificial Intelligence

Dr. Sumit Badotra is currently working as an Assistant Professor at the School of Computer Science and Engineering, at Bennett University, Greater Noida, India. He has around 7 years of research experience in software-defined networks (SDN and has published more than 25 journal articles and 30 papers published with national/international conferences. He has attended many national-level FDPs/workshops and has acted as a resource person as well. He is also an active reviewer in various reputed journals. Dr. Sarvesh Tanwar is an Associate Professor at Amity Institute of Information Technology (AIIT), Amity University, Noida. She is head of the AUN Blockchain & Data Security Research Lab. Dr. Tamwar has completed her M.Tech (CSE) degree from MMU, Mullana, and her Ph.D. in (CSE) from Mody University, Laxmangarh (Raj.). She has more than 15 years of teaching and research experience. Her area of research includes Public Key Infrastructure (PKI), Cryptography, Blockchain and Cyber Security. She has published more than 100 research papers in international journals and conferences, and she has filed 22 patents (18 published) and 2 copyrights in her relevant fields of interest. Dr. Tamwar is a Senior member of IEEE, a Life - Member, of the Cryptology Research Society of India (CRSI), Indian Institute of Statistics, Kolkata, India, and a member of the International Association of Computer Science and Information Technology (IACSIT), Singapore. Dr. Ashutosh Sharma is a Postdoctoral Fellow at the Southern Federal University, Russia as an international consultant in the Department of Research and Development. He has published more than 100 journal papers and his research interests are network management and intelligent systems, reliability, and risk engineering. Dr. Sharma had the honor of appearing consecutively (2021 and 2022) in the World’s Top 2% Scientist list published by Stanford University.

Part 1: Introduction of SDN. 1. Fundamental of SDN. 2. Scalability, Reliability Load Balancing Issues and Solutions for SDN. 3. Risk and Security Challenges in SDN Layers. Part 2: Software-Defined Networking with its Applications on the Internet of Things. 4. Use of SDN in Cloud Computing and Big Data. 5. The Impact of SDN as an Innovative Approach for Smart Healthcare Development, Traffic Monitoring Services, Telemedicine, Security, Agriculture, and Smart Grid Energy Savings. 6. A Complete Security Analysis of SDN-Based IoT Networks. 7. Use of SDN in Industrial Automation System. Part 3: AI with SDN. 8. Usage of AI and Machine Learning Techniques for Solving Potential Problems of SDN. 9. Network Anomaly Detection, Botnet Detection, and Traffic Re-Routing to a Network Honeypot in Networks Using SDN and ML. 10. Network Optimization and Traffic Management. 11. Integration of AI with SDN and IoT.