How to Calculate Network Number of Clusters in NS2

To calculate the number of clusters within a network using NS2 (Network Simulator 2) that normally encompasses grouping the nodes in the network according to their connectivity or proximity. A cluster is a group of nodes, which were closely connected, frequently with one node performing as the cluster head. The procedure of computing the clusters normally contains detecting how nodes are grouped together then counting the number of such groups (clusters). Here’s a simple guide to calculate the Number of Clusters in NS2:

Steps to Calculate the Number of Clusters in NS2

  1. Cluster Definition

Clusters are typically formed rely on proximity, connectivity, or protocol-based clustering (such as LEACH in wireless sensor networks). In the clustering protocols, every single cluster has a cluster head, in the cluster which coordinates the activities of the nodes.

  1. Set up the Simulation in NS2

Initially, configure a network topology then run the simulation. For cluster-based networks, like in Wireless Sensor Networks (WSN), we can be used a protocol, which supports clustering, like LEACH, to form a clusters actively.

Below is an example of configuring a simulation in NS2, which could be used for clustering (using a basic topology):

# Create NS2 simulator instance

set ns [new Simulator]

# Define nodes

set n0 [$ns node]

set n1 [$ns node]

set n2 [$ns node]

set n3 [$ns node]

set n4 [$ns node]

# Create links between nodes

$ns duplex-link $n0 $n1 1Mb 10ms DropTail

$ns duplex-link $n1 $n2 1Mb 10ms DropTail

$ns duplex-link $n2 $n3 1Mb 10ms DropTail

$ns duplex-link $n3 $n4 1Mb 10ms DropTail

# Define a wireless topology for clustering (if necessary)

# Assume clustering logic is handled by the clustering protocol

# Simulation end

$ns at 5.0 “finish”

proc finish {} {

global ns

$ns flush-trace

exit 0

}

# Run the simulation

$ns run

If we are using a particular clustering protocol then the nodes will automatically form a clusters during the simulation.

  1. Capture Trace Data

NS2 makes a trace file during the simulation. To determine the number of clusters, we can either:

  • We can be used the outcome of the clustering protocol that typically reports the cluster head nodes and their associated members.
  • Examine the trace file to determine how nodes are communicate and imply the clusters depends on the proximity or communication patterns.
  1. Determine Clustering Information

If a clustering protocol like LEACH or any other cluster-based protocol is used, the protocol itself should provide information about the clusters. For example, LEACH will elect cluster heads periodically, and all other nodes will join a cluster based on their distance to the cluster heads.

We can extract clustering details by:

  • Observing the control packets exchanged among cluster heads and its member nodes.
  • During the simulation, counting the number of single cluster heads.
  1. Extract Clustering Information from Trace File

To detect the clusters, we can analyse the trace file for particular events, like cluster head elections or communication are among the nodes within clusters.

Using AWK to Identify Cluster Heads:

If the trace file logs cluster formation then the cluster heads are typically marked by particular control packet exchanges or protocol messages. We can use AWK to process these cluster head messages.

Example AWK script to find cluster heads:

awk ‘

{

if ($4 == “CH” && $1 == “+”) { # Assuming CH marks cluster head messages

cluster_heads[$3] = 1

}

}

END {

print “Number of clusters: “, length(cluster_heads)

}’ out.tr

This AWK script:

  • Observes for control packets related cluster head (CH) messages.
  • Logs the single cluster heads.
  • Prints the number of single cluster heads that is equal to the number of clusters.
  1. Cluster-Based Protocol Output

If we are using a particular clustering protocol then the outcomes of the simulation should give the clustering informations, like:

  • Cluster head nodes.
  • Member nodes in each cluster.

For sample, if we can be used the LEACH or alternative clustering protocol then the protocol normally logs information regarding that nodes are cluster heads and how many clusters were formed.

  1. Manual Calculation of Clusters (Without a Protocol)

If we don’t use a predefined clustering protocol then we can be estimated the clusters manually rely on the node connectivity. For example, we can deliberate the nodes to be in the similar cluster if they are in a particular proximity (for wireless networks) or have direct communication links.

Here’s a simple approach:

  • We can use a distance-based metric or connectivity to group nodes into clusters.
  • Make a matrix of node distances or connectivity (i.e., which nodes can directly communicate with which other nodes).
  • We use a clustering algorithm (e.g., k-means, hierarchical clustering) to group the nodes into the clusters.

This approach could need more scripting and analysis, maybe outside NS2, using the tools such as Python or MATLAB.

  1. Post-Processing Clustering Data

When we have extracted the cluster details (either via the trace file or by running a clustering protocol) then we can be post-processed the data to count the number of clusters.

Using Python for Post-Processing:

Here is a basic Python script to count the number of clusters rely on the trace file:

cluster_heads = set()

with open(“out.tr”, “r”) as f:

for line in f:

data = line.split()

if data[1] == “+” and data[4] == “CH”:  # Assuming CH means cluster head

cluster_heads.add(data[2])  # Add cluster head node ID to set

print(f”Number of clusters: {len(cluster_heads)}”)

This script analyses the trace file, seeking the lines which show cluster head elections or cluster formation and then counts how many single cluster heads exist.

Summary

To estimate the number of clusters in NS2:

  1. Define Clustering: Make certain that have a clustering protocol or a process for detecting clusters.
  2. Run Simulation: Configure a network and run the simulation, if possible with a clustering protocol such as LEACH.
  3. Collect Trace Data: Analyse the trace file for data on cluster head elections and member nodes.
  4. Post-Process Data: We can use the tools such as AWK or Python to extract the number of clusters by counting single cluster heads or grouping nodes rely on connectivity.
  5. Analyze Results: The number of single cluster heads are corresponds to the number of clusters within the network.

The procedure to calculate and evaluate the Network Number of clusters in the simulation tool NS2 has been thoroughly explained above. Specific details will follow soon regarding this topic in another tool.

Reach out to us if you need help with your Network Number of Clusters in the NS2 tool. We can help you come up with cool project ideas and topics. Plus, we’ll assist you in doing a performance analysis, so just send us the details of your parameters!