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TUTORIAL – HALF DAY SESSION
APPLICATION OF MACHINE LEARNING AND DEEP LEARNING
ALGORITHMS IN SOFTWARE DEFINED NETWORKING RESEARCH

Mode: Onsite/online

Abstract: Software Defined Networking (SDN) has attracted researchers in last decade to a greater extent mainly because of its flexibility, robustness, and also the potential for developing sophisticated applications. SDN also promises many easy to manage applications and easy management of networks.

It is envisioned that there will be huge applications of SDN in all areas of networking including Internet of Things (IoT), Edge/Fog/Cloud, Information Centric Networks, and Cognitive Radio Networks, so on so forth.

However, considering the basic protocol developments necessary for SDN, it is found that there are still several issues that need urgent attention. Quality of Services (QoS) is one such area of concern even for SDN.

Again considering the popularity of Machine Learning (ML) algorithms in present time, it is also found in literature that there has been wide applications of ML algorithms in developing various protocols applicable for SDN that include traffic classification, routing, ensuring QoS in SDN etc. Similarly, Deep Learning (DL) algorithms are also increasingly being applied in solving networking issues connected to SDN.

In this tutorial, emphasis is on exploring applications of ML and DL algorithms in SDN research. The tutorial shall start from the basics of SDN and extend up to current research challenges in SDN research. Basics of ML and DL algorithms shall be highlighted. Then how ML and DL algorithms are being applied in SDN research shall be explored. Appropriate taxonomy related to application of ML and DL algorithms in ensuring QoS in SDN shall also be discussed. Simulation tools necessary for such research shall also be elaborated.

Learning Objectives: Attendees will be able

  • To understand the current research issues in SDN research
  • To learn how to choose ML and DL algorithms for solving persisting issues in SDN
  • To learn simulation tool like Mininet for SDN research along with Python

Draft Schedule:

  • Introduction to Software Defined Networking (SDN)
  • Applications of SDN
  • Current Research Challenges in SDN
  • Basics of Machine Learning and Deep Learning Algorithms
  • Applications of Machine Learning Algorithms in Ensuring QoS in SDN
  • Applications of Deep Learning Algorithms in Ensuring QoS in SDN
  • Simulation Experiments

Time Duration: 03 Hours (half day)

Maximum Number of Attendees: No limit.

Prospective Audience:Researchers, practitioners, Ph.D. students, P.G students, and any interested persons

Tutorial Speaker:

Dr. Hiren Kumar Deva Sarma is currently Professor in the Department of Information Technology, Sikkim Manipal Institute of Technology, Sikkim.

He received Bachelor of Engineering (B.E.) degree in Mechanical Engineering from Assam Engineering College (University of Gauhati, Guwahati, Assam) in 1998. He completed Master of Technology (M.Tech) in Information Technology from Tezpur University (Tezpur, Assam) in 2000. He received Doctor of Philosophy (Ph.D.) degree from Jadavpur University (Jadavpur, West Bengal), and under Department of Computer Science and Engineering, in 2013.

He has edited one book, four conference proceedings, co-authored three books, published more than eighty research papers in different International Journals, referred International and National Conferences of repute. He presented research paper in IEEE Carnahan Conference on Security Technology held at Albuquerque, USA (2004) and delivered tutorial in International Conference of repute in JAPAN (Sapporo, 2012).

He is the recipient of Young Scientist Award from International Union of Radio Science (URSI) in the XVIII General Assembly 2005, held at New Delhi, India and has received IEEE Early Adopter Award (USD 2000) in 2014. He was also invited by Indian Science Congress Association (ISCA) (for the prestigious Young Scientist Award) to their annual national conference in 2004 (Chandigarh) and 2006 (Hyderabad), respectively. He was selected for INSA summer research fellowship in 2013.

His current research interests are in the areas of wireless sensor networks, IoT, software defined networking, cognitive radio networks, network security, robotics, distributed computing and big data analytics.

Contact Details:

Prof. Hiren Kumar Deva Sarma, Member IEEE, Department of Information Technology
Sikkim Manipal Institute of Technology, Majitar, East Sikkim, Sikkim, India, PIN 737136
E-mail:hirenkdsarma@gmail.com, Mobile: +91 9733316230

Google Scholar Profile: https://scholar.google.co.in/citations?user=E_cH-VsAAAAJ&hl=en

Research Gate Profile: https://www.researchgate.net/profile/Hiren-Deva-Sarma

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