How to Implement QoS aware Clustering in OMNeT++

To implement QoS-aware clustering in OMNeT++ has encompasses to grouping nodes into clusters based on Quality of Service (QoS) requirements and make sure that data transmission within and among the clusters meets the particular QoS criteria. QoS-aware clustering is especially helpful in wireless sensor networks (WSNs), IoT networks, and mobile ad hoc networks (MANETs) where resources such as bandwidth, energy, and delay need to be enhanced.

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The below are the steps to implement the QoS-aware clustering in OMNeT++:

Steps to Implement QoS-aware Clustering in OMNeT++

Install OMNeT++ and INET Framework:
- Make sure that OMNeT++ and the INET framework are installed. We want to use frameworks such as Castalia if we are emulated wireless sensor networks (WSNs).
Define the Network Topology:
- Generate a network topology using a .ned file that particularly in nodes like sensors, devices and their connections. Nodes will be grouped into clusters based on QoS requirements.
Implement the QoS-aware Clustering Algorithm:
- To improve a clustering technique that groups nodes into clusters based on QoS metrics like bandwidth, latency, energy consumption, and node capability. The technique should choose cluster heads (CHs) based on these parameters.
Cluster Formation and Maintenance:
- Execute the logic for cluster formation, where nodes join clusters based on their QoS requirements. Furthermore, execute cluster maintenance that may conclude re-clustering, CH rotation, and maintaining node mobility or failures.
Integrate QoS Metrics into Clustering Decisions:
- Adjust the clustering technique to consider QoS parameters in the decision-making process make sure that the clusters formed can meet the QoS requirements of the applications execute on the network.
Simulate Different Traffic Types and QoS Requirements:
- Set up the various kinds of traffic within the network like real-time video, sensor data, and control messages. Each traffic type should have particular QoS requirements that the clustering algorithm must consider.
Configure Simulation Parameters:
- Use the .ini file to configure the metrics for the clustering techniques that involves QoS thresholds, cluster size, re-clustering intervals, and simulation time.
Run the Simulation and Analyse Results:
- Implement the simulation and measure the performance of the QoS-aware clustering algorithm and the parameters contain cluster stability, energy consumption, end-to-end delay, and how well the QoS requirements are met.

Example: Implementing a Basic QoS-aware Clustering Algorithm

Define the Network Topology in a .ned File

// QoSAwareClusteringNetwork.ned

package networkstructure;

import inet.node.inet.StandardHost;

network QoSAwareClusteringNetwork

{

submodules:

node[10]: StandardHost {

@display(“p=100,100”);

numApps = 1;

app[0].typename = “QoSAwareClusteringNode”;

}

Implement the QoS-aware Clustering Algorithm

Generate a C++ class for a simple QoS-aware clustering algorithm. This sample uses a simplified QoS metric based on energy and delay.

#include <omnetpp.h>

#include <inet/applications/base/ApplicationBase.h>

using namespace omnetpp;

using namespace inet;

class QoSAwareClusteringNode : public ApplicationBase

{

protected:

bool isClusterHead;

double energyLevel;

double delayRequirement;

virtual void initialize(int stage) override;

virtual void handleMessageWhenUp(cMessage *msg) override;

void joinCluster();

void formCluster();

double calculateQoSMetric();

public:

virtual int numInitStages() const override { return NUM_INIT_STAGES; }

};

Define_Module(QoSAwareClusteringNode);

void QoSAwareClusteringNode::initialize(int stage)

{

ApplicationBase::initialize(stage);

if (stage == INITSTAGE_APPLICATION_LAYER) {

isClusterHead = false;

energyLevel = par(“initialEnergy”).doubleValue();

delayRequirement = par(“delayRequirement”).doubleValue();

// Decide whether to become a cluster head based on QoS metrics

if (calculateQoSMetric() > par(“qosThreshold”).doubleValue()) {

formCluster();

} else {

joinCluster();

}

void QoSAwareClusteringNode::handleMessageWhenUp(cMessage *msg)

{

// Handle cluster-related messages (e.g., joining requests, data forwarding)

delete msg;

}

void QoSAwareClusteringNode::joinCluster()

{

EV << “Joining a cluster based on QoS metrics.” << endl;

// Logic to join an existing cluster, sending a request to the nearest CH

}

void QoSAwareClusteringNode::formCluster()

{

EV << “Forming a cluster as the Cluster Head (CH).” << endl;

isClusterHead = true;

// Logic to form a cluster and accept joining requests from other nodes

}

double QoSAwareClusteringNode::calculateQoSMetric()

{

// Example QoS metric: combination of energy level and delay requirement

return energyLevel / delayRequirement;

}

Modify Node Modules to Use the Clustering Algorithm

Expand the node modules to contains the clustering application.

simple StandardHost extends inet.node.inet.StandardHost

{

parameters:

@display(“i=device/sensor”);

numApps = 1;

app[0].typename = “QoSAwareClusteringNode”;

}

Configure the Simulation in the .ini File

network = networkstructure.QoSAwareClusteringNetwork

sim-time-limit = 100s

# Clustering node settings

**.node*.app[0].initialEnergy = 100J;

**.node*.app[0].delayRequirement = 0.1s;

**.node*.app[0].qosThreshold = 10.0; # QoS threshold for cluster head selection

Explanation of the Example

Network Topology (QoSAwareClusteringNetwork.ned):
- The network consists of 10 nodes (node[0] to node[9]), each running a QoS-aware clustering application.
QoS-aware Clustering Algorithm (QoSAwareClusteringNode.cc):
- The QoSAwareClusteringNode class executes basic clustering techniques that forms clusters based on QoS metrics such as energy level and delay requirement.
- Nodes with higher QoS metrics become cluster heads, while others join existing clusters.
Simulation Configuration (omnetpp.ini):
- The .ini file configures initial energy levels, delay requirements, and QoS thresholds for cluster head selection.

Running the Simulation

Compile project in OMNeT++ IDE and execute the simulation.
Use OMNeT++’s tools to monitor how clusters are formed, handled, and how the QoS-aware clustering technique performs in terms of energy consumption, delay, and cluster stability.

Extending the Example

Advanced QoS Metrics: Apply more complex QoS metrics that has bandwidth, jitter, and packet loss, to improve the clustering techniques.
Dynamic Clustering: Establish mobility or dynamic changes in network conditions to validate the clustering technique ability to adjust and maintain QoS.
Load Balancing: Execute load balancing between cluster heads to make sure even distribution of energy consumption and prolong network lifetime.
Inter-cluster Communication: Expand the techniques to handle inter-cluster communication that make sure QoS is maintained across the network.
Scalability: Extend the network to conclude more nodes and clusters that evaluate how the QoS-aware clustering scales with network size.

In the end of the module, we clearly learn about how the QoS aware clustering performance in the OMNeT++ tool that provides the enhanced resources over the network. If you need more details about the QOs aware clustering we will provide that too.