For network related studies, Ns-3 is a broadly deployed network simulator and it simulates SDN (Software-Defined Networking) by offering impactful characteristics. If you want to explore more potential ideas on SDN then read some of the concepts that are explained below. Numerous contemporary methodologies, instruments, and protocols are available to cater to the specific requirements of SDN projects. Reflecting on the application of Ns-3, we suggest some feasible project concepts on SDN:

  1. QoS-aware Traffic Engineering with OpenFlow
  • Explanation: By using OpenFlow with ns-3, it simulates QoS-aware traffic engineering solutions.
  • Characteristics:
  • In terms of built-in QoS tactics, it assigns the traffic.
  • It uses Yen’s or Dijkstra’s technique to execute path optimization.
  • Through OpenFlow messages, observe the traffic data.
  1. SDN-based Network Slicing for 5G Networks
  • Explanation: With the help of SDN-based network slicing, design a virtualized 5G network.
  • Characteristics:
  • Considering the various latency and bandwidth necessities, Ns-3simulates several network slices.
  • A slice orchestration technique is efficiently executed.
  • The resource allocation per slice is observed through this research.
  1. DDoS Detection and Mitigation in SDN Networks
  • Explanation: In an SDN platform, model a system for the purpose of identifying and reducing DDoS assaults.
  • Characteristics:
  • Legal and DDoS attack traffic are formulated through NS-3.
  • An outlier detection framework is executed.
  • NS-3 uses traffic flows to simulate attack mitigation tactics.
  1. SDN-enabled VANET (Vehicular Ad Hoc Network) Simulation
  • Explanation: A Vehicular Ad Hoc Network (VANET) is simulated in this research which is effectively managed through the SDN controller.
  • Characteristics:
  • This study encompasses the application of V2V (Vehicle-to-vehicle) and V2I (Vehicle-to-Infrastructure).
  • For centralized monitoring, Ns-3 synthesizes with an SDN controller.
  • The VANET traffic is efficiently observed and it improves the routing decisions.
  1. Energy-efficient Routing in Data Center Networks
  • Explanation: For data center networks with SDN, develop an energy-efficient routing protocol.
  • Characteristics:
  • Ns-3 simulates a fat-tree topology.
  • To reduce energy usage, it establishes a routing protocol.
  • Flow rules are efficiently upgraded by using OpenFlow.
  1. SDN-based IoT Network Management
  • Explanation: It makes use of SDN to design a scalable IoT network management system.
  • Characteristics:
  • Particularly for traffic like MQTT, this project includes a protocol handler.
  • Network policies are executed and it supervises the IoT traffic.
  • Actual-time traffic data collection is simulated dynamically.
  1. Machine Learning for Intelligent Traffic Management in SDN
  • Explanation: To categorize and handle traffic in an SDN network, this project implements machine learning models.
  • Characteristics:
  • Machine learning model is deployed for the process of gathering and categorizing network traffic.
  • Depending on anticipated patterns, it enhances the traffic flow.
  • Flow rules are executed in the SDN controller.
  1. Resilient Network Topology Management with SDN
  • Explanation: To adjust the network breakdowns in an effective manner, model a topology management system.
  • Characteristics:
  • Considering the indiscriminate link breakdowns, it simulates a network.
  • OpenFlow is applied for executing a topology discovery protocol.
  • It upgrades flow rules by means of Dijkstra’s algorithm.
  1. SDN and NFV Integration for Network Services Orchestration
  • Explanation: By synthesizing NFV and SDN, simulate a network services orchestration system.
  • Characteristics:
  • VNFs (Virtual Network Functions) are executed.
  • To manage traffic flow among VNFs, it implements OpenFlow.
  • On the basis of network policies, VNFs are orchestrated effectively.
  1. OpenFlow-based Secure Routing Protocol for IoT Networks
  • Explanation: Regarding the IoT networks, make use of OpenFlow to execute a secure routing protocol.
  • Characteristics:
  • Network traffic is encrypted and authorized dynamically.
  • Through OpenFlow rules, it observes and prevents the network from harmful traffic.
  • A secure network with ns-3 is simulated productively.

Initiating the Process with ns-3 SDN Simulation

  1. Download ns-3 and Features:
  • From the authentic repository, install the advanced version of ns-3.
  • And then, install OpenFlow and Ryu/POX/Floodlight SDN controllers.
  1. Build a Simple SDN Simulation:
  • By using OpenFlow switches and a remote controller, write an Ns-3 script.

Instance: Simple OpenFlow topology with ns-3

#include “ns3/core-module.h”

#include “ns3/network-module.h”

#include “ns3/internet-module.h”

#include “ns3/openflow-module.h”

#include “ns3/applications-module.h”

Using namespace ns3;

Int main (int argc, char *argv []) {

    // create the ns-3 nodes

    NodeContainer nodes;

    nodes.Create (4);

 // create the OpenFlow switches

    Ptr<Node> switch1 = nodes. Get (0);

    Ptr<Node> switch2 = nodes. Get (1);

 // create host devices

    NodeContainer hosts;

    hosts.Add (nodes.Get (2));

    hosts.Add (nodes.Get (3));

 // Set up the OpenFlow controller

    Ptr<ofi::Controller> controller = CreateObject<ofi::Controller> ();

// Set up OpenFlow switches and connect to the controller

 Ofi::SwitchHelper switchHelper;

switchHelper.InstallSwitch (switch1, controller);

    switchHelper.InstallSwitch (switch2, controller);

// Set up network devices for hosts and switches

 NetDeviceContainer devices;

    devices.Add (switchHelper.InstallDevice (hosts.Get (0), switch1));

    devices.Add (switchHelper.InstallDevice (hosts.Get (1), switch2));

// Install the Internet stack

 InternetStackHelper internet;

 internet.Install (hosts);

// Assign IP addresses

Ipv4AddressHelper ipv4;

ipv4.SetBase (“”, “”);

ipv4.Assign (devices);

// Run the simulation

Simulator::Run ();

Simulator::Destroy ();

Return 0;


  1. Design and Examine Your Application:
  • On the basic model, you can write and verify your particular project deployment.
  1. Evaluate Outcome and Organize with Documentation:
  • To evaluate performance, apply FlowMonitor or other ns-3 statistics.
  • File your result report and offer visualizations.

What are the SDN simulators currently accessible?

SDN (Software-Defined Networking) simulators are very essential to simulate the SDN environment. The prevalent and significant as well as available simulators, emulators and fundamental tools which engage in simulation process are follows:


  1. Ns-3
  • Specification: For research and academic objectives, Ns-3 is a highly adaptable discrete-event network simulator.
  • SDN Support:
  • Ns-3 simulator encompasses an OpenFlow module.
  • POX, Ryu and other external controllers are effectively supported here.
  1. EstiNet
  • Specification: EstiNet is a licensed network simulator or emulator.
  • SDN Support:
  • This simulator simulates OpenFlow networks.
  • Several SDN controllers such as ONOS and OpenDaylight are facilitated.
  1. GNS3
  • Specification: It is an effective graphical network simulator.
  • SDN Support:
  • Regarding SDN controllers such as Floodlight and OpenDaylight, GNS3 might be synthesized.
  • The emulation of network devices such as juniper routers and Cisco are enabled through this simulator.
  1. Mininet-WiFi
  • Specification: Specifically for wireless networks, it is an upgraded version of Mininet.
  • SDN Support:
  • It has the capacity to simulate wireless SDN networks.
  • With OpenFlow controllers, it can be easily compatible.
  1. OMNeT++
  • Specification: OMNeT++ is an extensible and modular discrete-event network simulator.
  • SDN Support:
  • By means of extensions, OMNeT++ assists OpenFlow networks.
  • SDN properties are incorporated through INET and CoRE4INET.


  1. Mininet
  • Definition: To develop a virtual network on a single machine, Mininet is a lightweight network emulator.
  • SDN Support:
  • Exterior controllers such as Ryu, POX, OpenDaylight and Floodlight are facilitated.
  1. GNS3
  • Definition: GNS3 is also helpful for the emulation process, as previously addressed.
  • SDN Support:
  • SDN controllers are implemented to emulate routers and switches.
  1. Containernet
  • Definition: It is an expansion of Mininet which inserts Docker container support.
  • SDN Support:
  • For exterior SDN controllers, Containernet is very compatible.
  1. EmuNet
  • Definition: EmuNet is a productive network emulation model.
  • SDN Support:
  • Synthesization of external controllers assists the SDN controllers.
  1. CORE (Common Open Research Emulator)
  • Definition: As similar to Mininet, CORE is also a lightweight network emulator.
  • SDN Support:
  • It can be synthesized with exterior SDN controllers.
  • CORE encompassed pre-defined OpenFlow support.

Specific Tools

  1. SDN Emulator (SDNE)
  • Explanation: For SDN examination, SDNE is an efficient emulator.
  • SDN Support:
  • POX and Floodlight controllers are accessed by SDNE.
  1. P4 Language Simulators (BMv2)
  • Explanation: P4 is a Behavioral Model Simulator (BMv2).
  • SDN Support:
  • P4 programmable data planes are the main highlights of BMv2.
  • With P4 Runtime-accessed SDN controllers, this tool is greatly suitable.
  1. OFNet
  • Explanation: Particularly for extensive-scale simulation, OFNet is a tailored SDN network emulator.
  • SDN Support:
  • This tool synthesizes dynamically with Ryu, ONOS and OpenDaylight.
SDN NS3 Thesis Topics

SDN NS3 Project Topics & Ideas 

We present the latest research concepts in SDN Projects and subjects that has disseminated for scholars. Our customers has achieved significant accomplishments through their collaboration with us. Stay connected with us for additional SDN NS3 Project Topics & Ideas. Feel free to address any uncertainties by email or phone call. Our support team will promptly reach out to you to assist scholars. Additionally, scholars can also utilize Google Meet for their convenience.

  1. Managing Smart Technologies with Software-Defined Networks for Routing and Security Challenges: A Survey
  2. Adaptive Partial Task Offloading and Virtual Resource Placement in SDN/NFV-Based Network Softwarization
  3. Artificial Intelligence Based Reliable Load Balancing Framework in Software-Defined Networks
  4. Optimal Deep Learning Driven Intrusion Detection in SDN-Enabled IoT Environment
  5. Adaptive Server Load Balancing in SDN Using PID Neural Network Controller
  6. Energy Efficient Load Balancing and Routing Using Multi-Objective Based Algorithm in WSN
  7. Load Balancing Algorithm for Migrating Switches in Software-Defined Vehicular Networks
  8. A Review on Software Defined Network (SDN) Based Network Security Enhancements
  9. A Novel Node Selection Method in Wireless Distributed Edge Storage Based on SDN and Multi-attribute Decision Model
  10. XFedHunter: An Explainable Federated Learning Framework for Advanced Persistent Threat Detection in SDN
  11. RackBlox: A Software-Defined Rack-Scale Storage System with Network-Storage Co-Design
  12. Adversarial Deep Reinforcement Learning for Cyber Security in Software Defined Networks
  13. Distributed Traffic Engineering in Hybrid Software Defined Networks: A Multi-agent Reinforcement Learning Framework
  14. A Survey of Software-Defined Smart Grid Networks: Security Threats and Defense Techniques
  15. Using Genetic Programming to Build Self-Adaptivity into Software-Defined Networks
  16. Software-defined quantum network using a QKD-secured SDN controller and encrypted messages
  17. Enabling Technologies for Programmable and Software-Defined Networks: Bolstering the Path Towards 6G
  18. A Security Evaluation Framework for Software-Defined Network Architectures in Data Center Environments
  19. Detection of DDoS Attacks in Software Defined Networking Using Machine Learning Models
  20. Smart Resource Allocation Model via Artificial Intelligence in Software Defined 6G Networks


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