Software Defined Networks detailed syllabus for Artificial Intelligence & Data Science (AI&DS) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the AI&DS students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Artificial Intelligence & Data Science 6th Sem scheme and its subjects, do visit AI&DS 6th Sem 2021 regulation scheme. For Professional Elective-III scheme and its subjects refer to AI&DS Professional Elective-III syllabus scheme. The detailed syllabus of software defined networks is as follows.
Course Objectives:
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Unit I
SDN: INTRODUCTION
Evolving Network Requirements – The SDN Approach – SDN architecture – SDN Data Plane , Control plane and Application Plane
Unit II
SDN DATA PLANE AND CONTROL PLANE-
Data Plane functions and protocols – OpenFLow Protocol – Flow Table – Control Plane Functions -Southbound Interface, Northbound Interface – SDN Controllers – Ryu, OpenDaylight, ONOS -Distributed Controllers
Unit III
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Unit IV
NETWORK FUNCTION VIRTUALIZATION
Network Virtualization – Virtual LANs – OpenFlow VLAN Support – NFV Concepts – Benefits and Requirements – Reference Architecture
Unit V
NFV FUNCTIONALITY
NFV Infrastructure – Virtualized Network Functions – NFV Management and Orchestration – NFV Use cases – SDN and NFV
Practical Exercises:
- Setup your own virtual SDN lab
- Create a simple mininet topology with SDN controller and use Wireshark to capture and visualize the OpenFlow messages such as OpenFlow FLOW MOD, PACKET IN, PACKET OUT etc.
- Create a SDN application that uses the Northbound API to program flow table rules on the switch for various use cases like L2 learning switch, Traffic Engineering, Firewall etc.
- Create a simple end-to-end network service with two VNFs using vim-emu
- https://github.com/containernet/vim-emu
- Install OSM and onboard and orchestrate network service.
i) Virtualbox/Mininet Environment for SDN – http://mininet.org
ii) https://www.kathara.org
iii) GNS3
Course Outcomes:
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Text Books:
- William Stallings, “Foundations of Modern Networking: SDN, NFV, QoE, loT and Cloud”, Pearson Education, 1st Edition, 2015.
Reference Books:
- Ken Gray, Thomas D. Nadeau, “Network Function Virtualization”, Morgan Kauffman, 2016.
- Thomas D Nadeau, Ken Gray, “SDN: Software Defined Networks”, O’Reilly Media, 2013.
- Fei Hu, “Network Innovation through OpenFlow and SDN: Principles and Design”, 1st Edition, CRC Press, 2014.
- Paul Goransson, Chuck Black Timothy Culver, “Software Defined Networks: A Comprehensive Approach”, 2nd Edition, Morgan Kaufmann Press, 2016.
- Oswald Coker, Siamak Azodolmolky, “Software-Defined Networking with OpenFlow”, 2nd Edition, O’Reilly Media, 2017.
For detailed syllabus of all the other subjects of Artificial Intelligence & Data Science 6th Sem, visit AI&DS 6th Sem subject syllabuses for 2021 regulation.
For all Artificial Intelligence & Data Science results, visit Anna University AI&DS all semester results direct link.