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# How to Calculate Network Accuracy in ns3

To calculate the accuracy in ns3, that usually relates to the accuracy of specified design or techniques inside the simulation. We try to measure the accuracy that can vary in liable scenarios. For instances, we simulated the Machine leaning approaches or task identification for these the accuracy would be the proportion of correctly classified across the total instance. We provide the interesting information about how the calculating the accuracy will perform in other simulation tools.

Here, we provide the step by step procedures on how to simulate the data transmission, evaluating the accuracy for the classification task model.

Steps to Calculate Accuracy in ns3

1. Set Up ns3 Environment:
• Make sure ns3 is installed
2. Create a New ns3 Script:
• Create a new script file in the scratch directory of ns3, e.g., accuracy_calculation.cc.
• In the script, conclude all the required ns3 headers.
4. Define Network Topology:
• Use multiple nodes to set up a network topology.
5. Implement Classification and Accuracy Calculation:
• Based on the results, mimic a classification task and compute the accuracy.

Example Code:

The given below are the sample code to illustrate how to implement the classification task and compute the accuracy in ns3. This is sample approach where the classification task is simulated by making random outcomes.

#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 <iostream>

using namespace ns3;

NS_LOG_COMPONENT_DEFINE (“AccuracyCalculationExample”);

void GenerateTraffic(Ptr<Socket> socket, Ptr<UniformRandomVariable> var, uint32_t pktSize, uint32_t pktCount)

{

if (pktCount > 0)

{

socket->Send(Create<Packet>(pktSize));

Simulator::Schedule(Seconds(var->GetValue(0.05, 0.1)), &GenerateTraffic, socket, var, pktSize, pktCount – 1);

}

}

void CalculateAccuracy(uint32_t totalPackets, uint32_t correctPackets)

{

double accuracy = static_cast<double>(correctPackets) / totalPackets * 100.0;

std::cout << “Total Packets: ” << totalPackets << std::endl;

std::cout << “Correctly Classified Packets: ” << correctPackets << std::endl;

std::cout << “Accuracy: ” << accuracy << “%” << std::endl;

}

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

{

uint32_t nNodes = 2; // Number of nodes

double simulationTime = 10.0; // Total simulation time in seconds

uint32_t totalPackets = 100; // Total number of packets to be sent

uint32_t correctPackets = 0; // Number of correctly classified packets

CommandLine cmd;

cmd.Parse(argc, argv);

NodeContainer nodes;

nodes.Create(nNodes);

PointToPointHelper pointToPoint;

pointToPoint.SetDeviceAttribute(“DataRate”, StringValue(“5Mbps”));

pointToPoint.SetChannelAttribute(“Delay”, StringValue(“2ms”));

NetDeviceContainer devices;

devices = pointToPoint.Install(nodes);

InternetStackHelper stack;

stack.Install(nodes);

uint16_t port = 9;

ApplicationContainer sinkApps = packetSinkHelper.Install(nodes.Get(1));

sinkApps.Start(Seconds(0.0));

sinkApps.Stop(Seconds(simulationTime));

Ptr<Socket>sourceSocket=Socket::CreateSocket(nodes.Get(0),TypeId::LookupByName(“ns3::UdpSocketFactory”));

Ptr<UniformRandomVariable> var = CreateObject<UniformRandomVariable>();

Simulator::ScheduleWithContext(sourceSocket->GetNode()->GetId(), Seconds(1.0), &GenerateTraffic, sourceSocket, var, 1024, totalPackets);

// Simulate classification by randomly determining if packets are classified correctly

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

{

if (var->GetValue(0, 1) > 0.5) // Assume a 50% chance of correct classification

{

correctPackets++;

}

}

Simulator::Stop(Seconds(simulationTime));

Simulator::Run();

Simulator::Destroy();

// Calculate and print accuracy

CalculateAccuracy(totalPackets, correctPackets);

return 0;

}

Explanation

Here, we provide the detailed structures for computing the accuracy for the classification task that are shown:

• Created nodes and configured a point-to-point network for communication.
• Set up the network with nodes connected using point-to-point links.
2. Applications:
• Installed a PacketSink application on one node to receive packets.
• Created a socket on another node to send packets.
3. Traffic Generation:
• Implemented the GenerateTraffic function to simulate sending packets from the source node to the sink node.
4. Simulate Classification:
• Simulated a simple classification task by randomly determining if packets are classified correctly with a 50% chance.
5. Accuracy Calculation:
• Implemented the CalculateAccuracy function to calculate the accuracy by dividing the number of correctly classified packets by the total number of packets.
6. Running the Simulation:
• The simulation runs, sending and receiving packets.
• After the simulation, the accuracy is calculated and printed.

Overall, we had calculated the accuracy for classification task has been successfully implemented and executed.

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