How to Implement Network Traffic Congestion in ns3

To implement the network traffic congestion in ns3, has encompasses to generate the scenarios where the network experiences high traffic load that prominent to congestion and it is emulated by creating a large number of data flows that overdo the network capacity.

Below is the procedure to implement the network traffic congestion in ns3.

Step-by-Step Implementation in ns3:

Step 1: Setup ns3 Environment

Make sure ns3 is installed in  the system and properly configured.

git clone https://gitlab.com/nsnam/ns-3-dev.git

cd ns-3-dev

./waf configure

./waf build

Step 2: Create the Simulation Script

We will create a simulation script that sets up a network with multiple nodes, generates traffic flows, and measures congestion metrics like packet loss and delay.

#include “ns3/core-module.h”

#include “ns3/network-module.h”

#include “ns3/internet-module.h”

#include “ns3/point-to-point-module.h”

#include “ns3/applications-module.h”

#include “ns3/flow-monitor-module.h”

using namespace ns3;

NS_LOG_COMPONENT_DEFINE (“TrafficCongestionExample”);

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

{

CommandLine cmd;

cmd.Parse (argc, argv);

// Create nodes

NodeContainer nodes;

nodes.Create (6);

// Create point-to-point links with limited bandwidth

PointToPointHelper pointToPoint;

pointToPoint.SetDeviceAttribute (“DataRate”, StringValue (“1Mbps”));

pointToPoint.SetChannelAttribute (“Delay”, StringValue (“10ms”));

NetDeviceContainer devices;

devices = pointToPoint.Install (nodes.Get (0), nodes.Get (1));

devices.Add (pointToPoint.Install (nodes.Get (1), nodes.Get (2)));

devices.Add (pointToPoint.Install (nodes.Get (2), nodes.Get (3)));

devices.Add (pointToPoint.Install (nodes.Get (3), nodes.Get (4)));

devices.Add (pointToPoint.Install (nodes.Get (4), nodes.Get (5)));

// Install the internet stack

InternetStackHelper stack;

stack.Install (nodes);

// Assign IP addresses

Ipv4AddressHelper address;

address.SetBase (“10.1.1.0”, “255.255.255.0”);

Ipv4InterfaceContainer interfaces;

interfaces = address.Assign (devices);

// Install applications to generate traffic

uint16_t port = 9;

OnOffHelper onoff (“ns3::UdpSocketFactory”, Address (InetSocketAddress (interfaces.GetAddress (5), port)));

onoff.SetConstantRate (DataRate (“2Mbps”)); // Higher than the link capacity to cause congestion

ApplicationContainer apps;

for (uint32_t i = 0; i < 5; ++i)

{

apps.Add (onoff.Install (nodes.Get (i)));

}

apps.Start (Seconds (1.0));

apps.Stop (Seconds (10.0));

// Install packet sink on the last node to receive packets

PacketSinkHelper sink (“ns3::UdpSocketFactory”, Address (InetSocketAddress (Ipv4Address::GetAny (), port)));

apps = sink.Install (nodes.Get (5));

apps.Start (Seconds (0.0));

apps.Stop (Seconds (10.0));

// Set up FlowMonitor to measure performance metrics

FlowMonitorHelper flowmon;

Ptr<FlowMonitor> monitor = flowmon.InstallAll();

// Run the simulation

Simulator::Stop (Seconds (10.0));

Simulator::Run ();

// Print per-flow statistics

monitor->CheckForLostPackets ();

Ptr<Ipv4FlowClassifier> classifier = DynamicCast<Ipv4FlowClassifier> (flowmon.GetClassifier ());

std::map<FlowId, FlowMonitor::FlowStats> stats = monitor->GetFlowStats ();

for (std::map<FlowId, FlowMonitor::FlowStats>::const_iterator i = stats.begin (); i != stats.end (); ++i)

{

Ipv4FlowClassifier::FiveTuple t = classifier->FindFlow (i->first);

NS_LOG_UNCOND (“Flow ” << i->first << ” (” << t.sourceAddress << ” -> ” << t.destinationAddress << “)”);

NS_LOG_UNCOND (”  Tx Packets: ” << i->second.txPackets);

NS_LOG_UNCOND (”  Tx Bytes:   ” << i->second.txBytes);

NS_LOG_UNCOND (”  Rx Packets: ” << i->second.rxPackets);

NS_LOG_UNCOND (”  Rx Bytes:   ” << i->second.rxBytes);

NS_LOG_UNCOND (”  Lost Packets: ” << i->second.lostPackets);

NS_LOG_UNCOND (”  Throughput: ” << i->second.rxBytes * 8.0 / (i->second.timeLastRxPacket.GetSeconds () – i->second.timeFirstTxPacket.GetSeconds ()) / 1024 / 1024 << ” Mbps”);

}

// Clean up

Simulator::Destroy ();

return 0;

}

Step 3: Compile and Run the Simulation

1. Compile the Simulation:

./waf configure –enable-examples

./waf build

Run the Simulation:

./waf –run scratch/<your-simulation-script>

Step 4: Analyse Results

The simulation script uses the FlowMonitor module to collect and print out statistics about the traffic flows. We analyse metrics like packet loss, throughput, and delay to realize the impact of congestion.

Additional Considerations

To extend the functionality of your network congestion simulation, consider the following:

1.      Varying Traffic Patterns

Implement different traffic patterns (e.g., TCP, varying data rates) to see how congestion affects different types of traffic.

2.      Congestion Control Mechanisms

Implement and compare different congestion control mechanisms (e.g., TCP variants like TCP Reno, TCP Cubic) to see how they perform under heavy traffic.

3.      Visualization

Use tools like NetAnim to visualize the network topology and traffic flow to better understand how congestion develops.

// Enable animation

AnimationInterface anim(“network-congestion-animation.xml”);

// Configure and run the simulation as before

Simulator::Stop (Seconds (10.0));

Simulator::Run ();

Simulator::Destroy ();

4.      Advanced Metrics

Collect and analyse additional metrics like jitter, packet delay variation, and fairness index.

From the script, we entirely explored how to generate the scenario to compile and run the network traffic congestion in a large number of data flows using the ns3 framework. We also deliver more interesting information about how the network traffic congestion will perform further tools.

Implementing Network Traffic Congestion in the ns3 tool can be challenging. Our experts are here to provide you with the best guidance on how to successfully apply it to your project.