SD-WAN (Software-Defined Wide Area Networking) is a significant software-defined approach to handle the WAN (Wide Area Network). We have completed an exceptional comparative analysis for your SD WAN thesis, conducted by top developers. All of our work is transparent, so feel free to contact us via phone or email with any questions or concerns you may have. We are dedicated to providing excellent responses to address your issues. Trust us with your thesis ideas, topics, and writing on SD WAN. In this article, we offer a model thesis proposal on SD-WAN:

Thesis Proposal: Software-Defined Wide Area Networking (SD-WAN)

  1. Introduction
  • Context: Due to the emergence of centralized control and programmability, SDN (Software-Defined Networking) regenerates conventional networking throughout the past few years. Effective and adaptive governance of geographically distributed networks are accessed through the approach of SD-WAN (Software-Defined Wide Area Networking) which expands its advantages to WANs (Wide Area Networks).
  • Problem Statement: Across vast distances, the conventional WANs address crucial problems like constrained scalability, weak application performance and network management. Regarding the perfect architecture patterns, effective traffic engineering and security, there is a necessity of further exploration even though SD-WAN provide hopeful results.
  • Research Questions:
  • How can SD-WAN architectures be enhanced for large-scale, multi-branch enterprise networks?
  • What are the efficient tactics for protecting SD-WAN applications?
  • How can effective traffic engineering develop the application performance in SD-WAN?
  1. Literature Review


  • Architectures:
  • Traditional WAN vs. SD-WAN architectures.
  • It includes key SD-WAN architectural components such as Edge Devices, controllers and Orchestrator.
  • Security:
  • Centralized policy management.
  • VPN tunneling and Encryption.
  • Traffic Engineering:
  • Multi-path routing algorithms.
  • Effective path selection and prioritization.
  • Research Gaps:
  • One of the key gaps is insufficiency of adaptable and secure SD-WAN models.
  • Inadequate level of interpretation in dynamic traffic engineering which has an effect on QoS.
  1. Objectives
  2. For extensive industries, it is significant to develop and assess a scalable SD-WAN architecture.
  3. As regards SD-WAN applications, design an effective security model.
  4. In SD-WAN architecture, execute and examine efficient tactics of traffic engineering.
  5. Methodology

Research Approach:

  • Phase 1: Architecture Design and Simulation Setup
  • A scalable SD-WAN architecture needs to be developed.
  • Use GNS3 or Mininet to build the architecture in a virtual platform.
  • Through REST API support, execute a basic SD-WAN controller.
  • Phase 2: Security Framework Development
  • Design a centralized policy management module.
  • Encryption and VPN tunneling protocols should be established.
  • To detect security susceptibilities, carry out vulnerability testing.
  • Phase 3: Traffic Engineering Implementation
  • Traffic prioritization techniques must be executed.
  • In terms of network conditions, create a module for effective path selection.
  • Phase 4: Evaluation and Comparative Analysis
  • Consider various network sizes to examine the scalability of architectures.
  • On the basis of network performance, assess the implications of the security model.
  • Based on application performance, evaluate the potential of traffic engineering tactics.

Simulation Tools and Platforms:

  • Emulators: GNS3 and Mininet.
  • Controllers: ONOS and OpenDaylight.
  • Traffic Generators: Wireshark, iperf and D-ITG.
  1. Expected Contributions
  2. For huge industries, a scalable SD-WAN architecture might be developed.
  3. Specifically for SD-Wan deployments, an extensive security model could be established.
  4. The application performance is advanced by implementing the tactics of dynamic traffic engineering.
  5. Work Schedule and Time Bound
  6. Phase 1 (Months 1-2):
  • Develop the SD-WAN architecture.
  • Virtual platforms have to be created.
  1. Phase 2 (Months 3-4):
  • Design the security model.
  • VPN tunneling and encryption protocols should be carried out.
  1. Phase 3 (Months 5-6):
  • Execute dynamic path selection and traffic prioritization.
  • Traffic engineering module requires to be formulated.
  1. Phase 4 (Months 7-8):
  • The security, performance and scalability need to be estimated.
  • Carry out a comparative analysis with conventional WAN (Wide Area Network).
  1. Phase 5 (Months 9-10):
  • Assure the final version of the thesis report and present the results.
  1. References
  2. Hu, Y., et al. (2021). A Comprehensive Security Framework for SD-WAN. Elsevier Computer Networks.
  3. Silva, L., & Passito, A. (2020). Dynamic Traffic Engineering in SD-WAN. IEEE Network.
  4. (2019). SD-WAN Overview and Architecture. Internet Engineering Task Force.

Can we implement software defined network SDN projects in NS2?

Yes! We can execute SDN (Software defined Network) projects in the NS-2 simulator. To simulate SDN-based activities, some extensions and patches are very essential. The process of implementing an SDN project in NS-2 is extensively illustrated here:

Conducting a SDN Project in NS-2

  1. Install NS-2

Initially, verify whether you install NS-2 and examine, if it is established accurately.

Install NS-2 on Ubuntu:

Sudo apt-get update

Sudo apt-get install ns2 –y

Install NS-2 Manually:

  • To download NS-2:


  • Derive and Install:

Tar -zxvf ns-allinone-2.35.tar.gz

Cd ns-allinone-2.35

. /install

  1. Insert OpenFlow/SDN Support to NS-2

Some extensions and patches are accessible in NS-2, even though it does not assist SDN controllers or OpenFlow in a direct way.

NS-2 Extension: SimpleSDN

  • Link: SimpleSDN GitHub Repository
  • Properties:
  • Use a basic SDN controller to offer simple SDN functionality.
  • Concentrate mainly on flow-based forwarding.


  1. Clone the SimpleSDN repository:

git clone

  1. In the SimpleSDN repository, click the ns-2.35 directory:

Cd SimpleSDN/ns-allinone-2.35/ns-2.35

  1. Use SimpleSDN patches to regenerate NS-2:

. /configure

Make clean


  1. Develop an SDN Network Topology

By considering the utilization of the SimpleSDN controller, design a network topology.

Sample TCL Script (simple_sdn.tcl)

# simple_sdn.tcl

# SDN Simulation with NS-2 and SimpleSDN

# set up simulator

Set ns [new Simulator]

# Create trace file

Set tracefile [open w]

$ns trace-all $tracefile

# set up network nodes

Set sdn_controller [$ns node]

Set switch1 [$ns node]

Set switch2 [$ns node]

Set host1 [$ns node]

Set host2 [$ns node]

Set host3 [$ns node]

# define link parameters

Set BW 10Mb

Set delay 10ms

Set queue DropTail

# create links between nodes

$ns duplex-link $sdn_controller $switch1 $BW $delay $queue

$ns duplex-link $sdn_controller $switch2 $BW $delay $queue

$ns duplex-link $switch1 $host1 $BW $delay $queue

$ns duplex-link $switch1 $host2 $BW $delay $queue

$ns duplex-link $switch2 $host3 $BW $delay $queue

# Set node positions (optional)

$ns at 0.0 “$sdn_controller set X_ 50”

$ns at 0.0 “$sdn_controller set Y_ 50”

$ns at 0.0 “$switch1 set X_ 100”

$ns at 0.0 “$switch1 set Y_ 50”

$ns at 0.0 “$switch2 set X_ 150”

$ns at 0.0 “$switch2 set Y_ 50”

$ns at 0.0 “$host1 set X_ 100”

$ns at 0.0 “$host1 set Y_ 100”

$ns at 0.0 “$host2 set X_ 100”

$ns at 0.0 “$host2 set Y_ 150”

$ns at 0.0 “$host3 set X_ 150”

$ns at 0.0 “$host3 set Y_ 100”

# set up TCP traffic

Set tcp [new Agent/TCP]

Set sink [new Agent/TCPSink]

$ns attach-agent $host1 $tcp

$ns attach-agent $host3 $sink

$ns connect $tcp $sink

Set ftp [new Application/FTP]

$ftp attach-agent $tcp

$ns at 1.0 “$ftp start”

# Run the simulation

$ns at 10.0 “finish”

Proc finish {} {

    Global ns tracefile

    $ns flush-trace

    Close $tracefile

    Exit 0


$ns run

  1. Execute the SDN Simulation
  2. Crucially, save the simple_sdn.tcl script.
  3. Apply Ns-2 to execute simulation:

ns simple_sdn.tcl

  1. Assess the Results

Evaluate the outcome by using the following elements:

  • AWK Scripts: You can deploy AWK scripts to filter and process the trace files.
  • Network Animator (NAM): It can be particularly applicable for visual network analysis.

Instance of AWK Script (analyze.awk):

# analyze.awk

# Extract throughput information from trace file


    FS = ” “

    total_bytes = 0

    start_time = 1.0

    end_time = 10.0


($1 == “r” && $4 == “tcp” && $7 == “ACK”) {

    If ($2 >= start_time && $2 <= end_time) {

        total_bytes += $10




    Throughput = total_bytes * 8 / (end_time – start_time) / 1e6

    Print “Throughput (Mbps): ” throughput


Run AWK Script:

Awk -f analyze.awk


You can simulate and carry out a valuable exploration, as NS-2 provides extensions and patches like SimpleSDN, even though it does not support SDN directly.

Crucial Measures:

  1. Download NS-2 and implement SDN patches or extensions.
  2. Use TCL scripting to design an SDN topology.
  3. Execute the simulation and evaluate the performance.
SD WAN Thesis Topics

SD WAN Thesis Topics & Ideas

We have helped scholars with various SD WAN Thesis Topics & Ideas at Reach out to us for a unique research solution and well-structured thesis writing services. Contact us without hesitation.

  1. QoS-aware network operating system for software defined networking with generalized OpenFlows
  2. Efficient DDoS detection based on K-FKNN in software defined networks
  3. Performances of OpenFlow-based software-defined networks: an overview
  4. MNOS: a mimic network operating system for software defined networks
  5. Toward a cyber resilient and secure microgrid using software-defined networking
  6. Wireless software-defined networks (W-SDNs) and network function virtualization (NFV) for 5G cellular systems: An overview and qualitative evaluation
  7. 5G-EmPOWER: A Software-Defined Networking Platform for 5G Radio Access Networks
  8. Content-centric networking management based on software defined networks: survey
  9. A deep CNN ensemble framework for efficient DDoS attack detection in software defined networks
  10. Achieving high scalability through hybrid switching in software-defined networking
  11. Performance Analysis of Software-Defined Network Switch Using Model
  12. Extending Dijkstra’s shortest path algorithm for software defined networking
  13. Mind the gap: Monitoring the control-data plane consistency in software defined networks
  14. Wedgetail: An intrusion prevention system for the data plane of software defined networks
  15. Achieving end-to-end real-time quality of service with software defined networking
  16. Modeling, detecting, and mitigating threats against industrial healthcare systems: a combined software defined networking and reinforcement learning approach
  17. DDoS attack detection method based on improved KNN with the degree of DDoS attack in software-defined networks
  18. Network coded software defined networking: Enabling 5G transmission and storage networks
  19. Detection of distributed denial of service attacks using machine learning algorithms in software defined networks
  20. Enabling layer 2 pathlet tracing through context encoding in software-defined networking

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