How to Calculate Network Hubs in omnet++

To calculate and identify the network hubs in OMNeT++ includes verifying which nodes in a network have the maximum degree of centrality or connectivity. A hub in a network is normally a node with a high number of connections (high degree) or a node that plays a serious role in the overall network structure (high centrality).

Step-by-Step Implementations:

1. Understand Network Hubs

A network hub can be described in various paths based on the metric used:

• Degree Centrality: A hub is a node with the maximum number of direct relations to other nodes.
• Betweenness Centrality: A hub is a node that often acts as a bridge along the shortest path among two other nodes.
• Closeness Centrality: A hub is a node that has the shortest average distance to all other nodes in the network.

2. Set up the Network in OMNeT++

Make sure that the network is properly set up in OMNeT++ with nodes and connections specified in a .ned file.

Example: Define a Simple Network in NED

network SimpleNetwork {

submodules:

node[5]: Node;  // A network with 5 nodes

connections:

node[0].out++ –> node[1].in++;

node[1].out++ –> node[2].in++;

node[2].out++ –> node[3].in++;

node[3].out++ –> node[4].in++;

node[0].out++ –> node[4].in++;

}

3. Calculate Degree Centrality

To evaluate degree centrality, we count the number of connections each node has.

Example: Implementing Degree Centrality Calculation

#include <omnetpp.h>

using namespace omnetpp;

class Node : public cSimpleModule {

private:

int degree = 0;  // Degree centrality

protected:

virtual void initialize() override {

// Count the number of connected gates (degree)

for (cModule::GateIterator it(this); !it.end(); ++it) {

cGate *gate = *it;

if (gate->isConnectedOutside()) {

degree++;

}

}

// Record the degree centrality

EV << “Node ” << getIndex() << ” has degree centrality: ” << degree << endl;

recordScalar(“Degree Centrality”, degree);

}

};

Define_Module(Node);

4. Identify Hubs Based on Degree Centrality

The nodes with the highest degree centrality can be identified as hubs after running the simulation.

5. Advanced Metrics: Betweenness and Closeness Centrality

If we need to estimate more advanced centrality metrics like betweenness or closeness, we may want to implement further logic to calculate shortest paths and examine the role of each node in those paths.

Example: Conceptual Overview for Betweenness Centrality

Betweenness centrality is evaluated by determining how often a node appears on the shortest path among any two other nodes. To compute this:

1. Discover all shortest paths among pairs of nodes in the network.
2. Count how many of these paths pass over each node.
3. Normalize the count based on the total number of shortest paths.

Example: Conceptual Overview for Closeness Centrality

Closeness centrality is computed as the reciprocal of the sum of the shortest path distances from a node to all other nodes in the network:

1. Evaluate the shortest path from the node to every other node.
2. Sum these distances.
3. Take the reciprocal of this sum.

6. Post-Simulation Analysis

After calculating centrality metrics, use OMNeT++’s built-in analysis tools or transfer the data to further analyse the network’s structure. Nodes with the maximum centrality values can be considered as hubs.

7. Example Scenario

Given below is a set-up where we calculate degree centrality and identify the hubs in a simple network:

network HubExample {

submodules:

node[6]: Node;

connections:

node[0].out++ –> node[1].in++;

node[1].out++ –> node[2].in++;

node[2].out++ –> node[3].in++;

node[3].out++ –> node[4].in++;

node[4].out++ –> node[5].in++;

node[5].out++ –> node[0].in++;  // Creates a cycle

node[0].out++ –> node[2].in++;  // Node 0 connects to multiple nodes

}

8. Identify Hubs Post-Simulation

After running the simulation, analysis the scalar data for degree centrality. The nodes with the maximum degree centrality are the hubs.

In the above informations, we are learned and get knowledge through the procedure to calculate and analyse the Network Hubs using OMNeT++. More comprehensive informations will be provided depends on your desires.

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