How to Calculate Network Number of clusters in ns3

To calculate the number of clusters in a network in ns3, we need to simulate a clustering algorithm and then determine how many clusters are formed based on the network topology and the clustering criteria. The steps for achieving this are listed below.

Steps for calculating number of clusters

1. Set up the simulation :

• Make sure that ns3 is installed in the computer. If not, install it and include necessary modules.

2. Define Network Topology:

• create the network topology by incorporating nodes and links.

3. Implement a Clustering Algorithm:

• To form clusters within the network, Implement or use an existing clustering algorithm.

4. Determine the Number of Clusters:

• To count the number of clusters formed, analyze the results of the clustering algorithm.

Example code

Here is an example to set up a basic simulation to calculate the number of clusters formed using a basic clustering algorithm in ns3. In this example we will use a simplified version of a clustering algorithm based on node IDs for illustrative purposes.

#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”

using namespace ns3;

NS_LOG_COMPONENT_DEFINE (“NetworkClusteringExample”);

void CreateClusters (NodeContainer nodes, std::map<uint32_t, uint32_t> &clusterMap)

{

uint32_t clusterId = 0;

for (NodeContainer::Iterator i = nodes.Begin (); i != nodes.End (); ++i)

{

Ptr<Node> node = *i;

clusterMap[node->GetId ()] = clusterId;

clusterId++;

}

}

uint32_t CountClusters (std::map<uint32_t, uint32_t> &clusterMap)

{

std::set<uint32_t> uniqueClusters;

for (auto const &entry : clusterMap)

{

uniqueClusters.insert (entry.second);

}

return uniqueClusters.size ();

}

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

{

CommandLine cmd;

cmd.Parse (argc, argv);

Time::SetResolution (Time::NS);

NodeContainer nodes;

nodes.Create (10); // Create 10 nodes

PointToPointHelper pointToPoint;

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

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

NetDeviceContainer devices;

for (uint32_t i = 0; i < nodes.GetN () – 1; ++i)

{

for (uint32_t j = i + 1; j < nodes.GetN (); ++j)

{

devices.Add (pointToPoint.Install (NodeContainer (nodes.Get (i), nodes.Get (j))));

}

}

InternetStackHelper stack;

stack.Install (nodes);

Ipv4AddressHelper address;

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

address.Assign (devices);

Simulator::Stop (Seconds (1.0));

Simulator::Run ();

std::map<uint32_t, uint32_t> clusterMap;

CreateClusters (nodes, clusterMap);

uint32_t numberOfClusters = CountClusters (clusterMap);

NS_LOG_UNCOND (“Number of Clusters: ” << numberOfClusters);

Simulator::Destroy ();

return 0;

}

Explanation

1. Setup:

Created ten nodes with full mesh connectivity between the nodes using point-to-point links.

1. Clustering Algorithm:

The CreateClusters function is used to assign a unique cluster ID to each node, effectively treating each node as its own cluster for simplicity. In a real-world scenario, we may implement a more sophisticated clustering algorithm.

1. Count Clusters:

The CountClusters function is used to count the number of unique clusters by inserting the cluster IDs into a set and then return the size of the set.

1. Output:

The number of clusters are printed to the console.

Running the Simulation

Compile and run the simulation using the following commands:

./waf configure

./waf build

./waf –run your-script-name

Replace your-script-name with the actual name of your script file.

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