MININET DDOS Simulation team have been greatly benefited for scholars as we have a well-structured team of subject expert guide to handle all your doubts in MININET DDOS. By adhering to our professional advice and instructions, there will be no obstacles preventing you from attaining your doctorate. We effortlessly handle topic selection and thesis writing in all areas of MININET DDOS Simulation. To get best simulation results we will be your right partner. Your journey towards obtaining a PhD will be seamless and prosperous. Our objective is to uncover valuable information and draw meaningful conclusions for your MININET project. Through the utilization of Mininet, to carry out a Distributed Denial-of-Service (DDoS) attack simulation and performance analysis, you must adhere to these major procedures:

  1. Configure Mininet: On your framework, it is advisable to install and arrange Mininet.
  2. Construct a Network Topology: A virtual network topology has to be developed in such a manner that depicts your scenario in an explicit way.
  3. Apply DDoS Attack: Through the utilization of tools such as Scapy or hping3, construct a DDos attack simulation.
  4. Assess Performance Metrics: It is appreciable to gather and examine significant network performance parameters.
  5. Examine the Outcomes: In order to evaluate the influence, contrast the outcomes before, during, and after the DDoS attack.

Step-by-Step Guide

Step 1: Configuring Mininet

By means of employing the following procedures, install Mininet on your Linux machine.

# Clone the Mininet repo

git clone

# Install Mininet

cd mininet

util/ –a

Step 2: Construct Network Topology

Encompassing numerous switches and hosts, develop a Mininet topology. For example, develop a basic topology file

from mininet.topo import Topo

from import Mininet

from mininet.node import OVSController

from mininet.cli import CLI

class DDOSTopology(Topo):

    def build(self):

        switch = self.addSwitch(‘s1’)

        # Add normal hosts

        for i in range(1, 4):

            host = self.addHost(f’h{i}’)

            self.addLink(host, switch)

        # Add attacker hosts

        for j in range(4, 7):

            attacker = self.addHost(f’h{j}’)

            self.addLink(attacker, switch)

def start_network():

    topo = DDOSTopology()

    net = Mininet(topo=topo, controller=OVSController)




if __name__ == ‘__main__’:


Step 3: Apply DDoS Attack

To produce DDoS traffic from the assaulting hosts such as h4, h5, h6 in this situation, aim to employ tools such as Scapy or hping3. It is appreciable to assure that these tools are installed on your framework:

# Install hping3

sudo apt-get install hping3

# Install hping3

sudo apt-get install hping3

Launch a SYN flood attack from the attacking hosts:

# On attacker host h4, h5, h6

h4 hping3 -S -p 80 –flood

h5 hping3 -S -p 80 –flood

h6 hping3 -S -p 80 –flood

Step 4: Assess Performance Metrics

You can assess network performance by means of employing iperf tool, before beginning the DDoS assault.

# On server host h1

iperf -s

# On client host h2

iperf -c h1

To evaluate the influence, document the latency and bandwidth before and after initiating the assault.

For packet-level exploration, you can also utilize tools such as Wireshark or tcpdump.

# On any host to capture packets

tcpdump -i any -w ddos_traffic.pcap

Step 5: Examine the Outcomes

  1. Network Bandwidth Analysis: Focus on contrasting the iperf outcomes before and during the assault.
  2. Packet Capture Analysis: Through employing Wireshark, examine the packet capture (ddos_traffic.pcap).
  3. Latency Measurements: By means of ping, assess latency before and during the assault.

Python-Based Analysis with Scapy

In order to investigate traffic trends, employ Scapy.

from scapy.all import rdpcap

packets = rdpcap(“ddos_traffic.pcap”)

# Process packets here to analyze traffic patterns

Performance Analysis Report Structure

  1. Introduction: This section explains the goal and focus of the DDoS attack simulation.
  2. Methodology:
  • Network Topology
  • Attack Policy
  • Assessment Tools
  1. Results:
  • Bandwidth Exploration (Tables, Graphs)
  • Packet Exploration (Frequency, Types)
  • Latency Parameters
  1. Conclusion: Focus on outlining the outcomes and influence of DDoS assault.
  2. Recommendations: Specifically, for reduction policies or upcoming research regions, it offers beneficial recommendations.

How can I run multiple SDN controllers Floodlight Ryu ODL etc for a topology in Mininet?

There are many steps involved to execute numerous SDN controllers in Mininet. We suggest a stepwise instruction based on how to perform this in effective manner:

Steps to Run Multiple SDN Controllers with Mininet

  1. Install the Controllers: It is appreciable to make sure that every controller is installed on your system.
  2. Configure Controllers: Mainly, for every controller arrange the listening ports and protocols.
  3. Create a Mininet Topology: A topology has to be modelled in such a way that can be regulated by numerous controllers.
  4. Assign Controllers to Specific Switches: To allocate individual controllers to certain switches, employ the Mininet API.

Instance Configuration

  1. Install the Controllers

Aim to assure that OpenDaylight, Floodlight, and Ryu are installed in a correct manner.



# Install Java if you haven’t already

sudo apt install openjdk-11-jdk

# Clone and build Floodlight

git clone

cd floodlight

./gradlew shadowJar


# Install Ryu

pip install ryu


# Download and extract OpenDaylight


tar -zxvf distribution-karaf-0.10.2-Helium.tar.gz

cd distribution-karaf-0.10.2-Helium

# Start OpenDaylight


  1. Configure Controllers


# Run Floodlight

java -jar target/floodlight.jar

Floodlight will begin listening on port 6653.


# Run Ryu controller

ryu-manager –ofp-tcp-listen-port 6654

OpenDaylight By default, OpenDaylight will listen on port 6633.

  1. Create a Mininet Topology

To specify the network, it is better to develop a Mininet topology script such as

from import Mininet

from mininet.topo import Topo

from mininet.node import RemoteController, OVSSwitch

from mininet.cli import CLI

from mininet.log import setLogLevel

class MultiControllerTopo(Topo):

    def build(self):

        # Create switches

        s1 = self.addSwitch(‘s1′, protocols=’OpenFlow13’)

        s2 = self.addSwitch(‘s2′, protocols=’OpenFlow13’)

        s3 = self.addSwitch(‘s3′, protocols=’OpenFlow13’)

        # Create hosts

        h1 = self.addHost(‘h1’)

        h2 = self.addHost(‘h2’)

        h3 = self.addHost(‘h3’)

        h4 = self.addHost(‘h4’)

        # Add links between switches and hosts

        self.addLink(h1, s1)

        self.addLink(h2, s1)

        self.addLink(h3, s2)

        self.addLink(h4, s3)

        # Add links between switches

        self.addLink(s1, s2)

        self.addLink(s2, s3)

def start_network():

    topo = MultiControllerTopo()

    net = Mininet(topo=topo, switch=OVSSwitch)

    # Define controllers

    floodlight = RemoteController(‘floodlight’, ip=’′, port=6653)

    ryu = RemoteController(‘ryu’, ip=’′, port=6654)

    odl = RemoteController(‘opendaylight’, ip=’′, port=6633)

    # Add controllers to Mininet    net.addController(floodlight)



    # Associate specific controllers with switches    net.get(‘s1’).start([floodlight])






if __name__ == ‘__main__’:



  1. Run the Topology

By means of script, execute the Mininet topology:

sudo python3

MININET DDOS Simulation Support

MININET DDOS Simulation Topics

Discover a range of unique MININET DDOS Simulation topics that encompass various challenges. Our proficient team effortlessly overcomes several types of obstacles encountered during your MININET DDOS Simulation. Avail the expertise of our extensive resource team to effectively address your modelling and simulation requirements.

  1. DDoS Simulation: Empowering Targets through Simulated Attacks
  2. A Simulation based analysis study for DDoS attacks on Computer Networks
  3. Developing and experimenting simulation model of DDoS attacks in IIoT networks using Python
  4. Design and Implementation of DDoS Attack and Defense Simulation Subsystem Based on Mininet
  5. Modelling Lanchester Style DDOS Attack and Defense
  6. Consensus-based Frequency Control of a Cyber-physical Power System under Two Types of DDoS Attacks
  7. Real-time Detection of DDoS Attacks Based on Hurst Index
  8. Exploring Realistic VANET Simulations for Anomaly Detection of DDoS Attacks
  9. Factors Effecting Businesses due to Distributed Denial of Service (DDoS) Attack
  10. Multi-Dimensional Security Indicator Design and Optimization for DDoS Detection in Edge Computing
  11. Enhancing Resilience against DDoS Attacks in SDN -based Supply Chain Networks Using Machine Learning
  12. DDOS Attack Detection Accuracy Improvement in Software Defined Network (SDN) Using Ensemble Classification
  13. Toward Adaptive DDoS-Filtering Rule Generation
  14. Applying Dynamic Threshold in SDN to Detect DDoS Attacks
  15. An Activatable DDoS Defense for Wireless Sensor Networks
  16. Controller-Targeted DDoS Attack Detection and Mitigation in Software-Defined Internet of Vehicles (SD-IoV)
  17. DDoS and Flash Event Detection in Higher Bandwidth SDN-IoT using Multiagent Reinforcement Learning
  18. Securing IIoT Against DDoS attacks: A Stochastic Approach
  19. Simulation of distributed denial of service attack against ethereum smart contract on the blockchain
  20. Classification of DDoS Attacks and Flash Events using Source IP Entropy and Traffic Cluster Entropy


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