How to Implement Network Clustering in OMNeT++

To implement the network clustering in OMNeT++ has encompasses establishing a network into clusters where nodes in each cluster communicate with a designated cluster head. It is a general method in mobile ad-hoc networks (MANETs), wireless sensor networks (WSNs), and other distributed systems to increase network scalability, energy efficiency, and management.

The following step-by-step guide to executing network clustering in OMNeT++ using the INET framework:

Step-by-Step Implementations:

1. Set Up OMNeT++ and INET Framework:

• Install OMNeT++: Make sure OMNeT++ is installed and configured on the system.
• Install INET Framework: Download and install the INET framework, which offers models for network nodes, communication protocols, and mobility.

2. Define the Network Topology:

Make a network topology where several nodes are organized into clusters. Each cluster has a cluster head responsible for intra-cluster communication and probably for sending data to a central base station or other clusters.

Example NED File (ClusteredNetwork.ned):

package mynetwork;

import inet.node.inet.StandardHost;

import inet.node.inet.Router;

import inet.mobility.static.GridMobility;

network ClusteredNetwork

{

parameters:

int numClusters = default(3); // Number of clusters

int nodesPerCluster = default(5); // Number of nodes per cluster

submodules:

clusterHead[numClusters]: StandardHost {

@display(“p=200,200”);

}

node[numClusters*nodesPerCluster]: StandardHost {

@display(“p=200,200”);

mobility: <GridMobility> {

playgroundSizeX = 1000m;

playgroundSizeY = 1000m;

deltaX = 100m;

deltaY = 100m;

}

}

router: Router {

@display(“p=500,500”);

}

connections allowunconnected:

// Connect cluster heads to the router

for i=0..numClusters-1 {

clusterHead[i].pppg++ <–> ethernetLine <–> router.pppg++;

}

// Connect nodes to their respective cluster heads

for i=0..numClusters*nodesPerCluster-1 {

node[i].pppg++ <–> ethernetLine <–> clusterHead[i/nodesPerCluster].pppg++;

}

}

In this example:

• clusterHead[]: Signifies the cluster heads.
• node[]: Denotes the regular nodes that belong to clusters.
• router: Performs as a central router or base station relating cluster heads.

3. Implement Clustering Logic:

Nodes essential to communicate with their respective cluster heads in a clustered network. It contains designating cluster heads, assigning nodes to clusters, and make sure that all communication in a cluster is routed over the cluster head.

Example: Basic Cluster Head Selection

void NetworkNode::initialize() {

if (isClusterHead) {

// Code for cluster head initialization

EV << “I am the cluster head\n”;

} else {

// Code for regular node initialization

EV << “I am a regular node\n”;

scheduleAt(simTime() + uniform(1, 5), sendDataMsg);  // Schedule data sending

}

}

void NetworkNode::handleMessage(cMessage *msg) {

if (msg == sendDataMsg) {

// Regular node sends data to cluster head

if (!isClusterHead) {

auto packet = createPacket(“DataPacket”);

send(packet, “pppg$o”);  // Send to cluster head

}

} else if (isClusterHead) {

// Cluster head processes incoming data

EV << “Cluster head received data\n”;

forwardDataToRouter(msg);

}

}

void NetworkNode::forwardDataToRouter(cMessage *msg) {

// Cluster head forwards data to the central router

send(msg, “pppg$o”);

}

In this code:

• initialize(): Determines if the node is a regular node or a cluster head.
• handleMessage():Handles the sending of data from cluster heads to the central router and from regular nodes to cluster heads.
• forwardDataToRouter():Manages sending data from the cluster head to the central router.

4. Simulate Cluster Formation:

Cluster formation can be static (predefined) or dynamic (nodes elect cluster heads at runtime). In a dynamic situation, nodes can use numerous algorithms, like the Low-Energy Adaptive Clustering Hierarchy (LEACH) or other clustering algorithms, to designated cluster heads.

Example: Dynamic Cluster Head Election (Simple)

void NetworkNode::initialize() {

if (uniform(0, 1) < 0.2) {  // 20% chance to become cluster head

isClusterHead = true;

EV << “Elected as cluster head\n”;

} else {

isClusterHead = false;

EV << “Not a cluster head, joining a cluster\n”;

}

scheduleAt(simTime() + uniform(1, 5), sendDataMsg);

}

In this simple election process, each node has a 20% chance of becoming a cluster head.

5. Simulate Communication Within Clusters:

Nodes would only communicate with their designated cluster head. The cluster head can then aggregate the data and transfer it to the central router.

Example: Aggregation of Data at Cluster Head

void NetworkNode::handleMessage(cMessage *msg) {

if (!isClusterHead) {

// Regular node sends data to cluster head

auto packet = createPacket(“DataPacket”);

send(packet, “pppg$o”);

} else {

// Cluster head aggregates data and forwards it

aggregatedData += extractDataFromPacket(msg);

if (simTime() >= nextForwardTime) {

auto packet = createPacket(“AggregatedDataPacket”);

send(packet, “pppg$o”);

aggregatedData = 0;  // Reset after forwarding

nextForwardTime = simTime() + 10;  // Schedule next forwarding time

}

}

}

6. Monitor and Analyse Cluster Performance:

Observe the act of the clustering mechanism by analysing metrics like network scalability, data aggregation efficiency, energy consumption, and cluster formation time.

Example Configuration for Monitoring Cluster Performance:

[General]

network = ClusteredNetwork

**.clusterHead[*].app[0].energyConsumption.recordScalar = true

**.clusterHead[*].app[0].aggregatedData.recordScalar = true

**.node[*].app[0].sendInterval = 1s

This configuration records the energy consumption and data aggregation at the cluster heads.

7. Simulate and Analyse the System:

• Run the Simulation: Begin the simulation and monitor how data is aggregated and forwarded by cluster heads, how clusters form, and how nodes communicate in the clusters.
• Analyse the Results: Examine the recorded metrics to assess the efficiency of the clustering algorithm and the performance of the network, after the simulation.

8. Extend the Model:

• Dynamic Clustering: Execute more sophisticated clustering algorithms, like LEACH, K-Means, or other clustering protocols that familiarise to varying network conditions.
• Energy Management: Incorporate energy management strategies to enhance the energy consumption of nodes, specifically in battery-powered networks.
• Fault Tolerance: Append mechanisms to manage cluster head failures and re-election processes.

In conclusion, we had showed complete procedure and their sample instances is helps to execute the Network Clustering in OMNeT++ using the INET framework. More details will be offered based on your requests.

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