How to Implement Network Social Network Analysis in OMNeT++
To implement Social Network Analysis (SNA) in OMNeT++ has needs to emulate a network of nodes that signify the individuals or entities within a social network and evaluating their interactions, relationships, and behaviours and this can encompasses the tasks like measuring centrality, identifying communities, or examining the flow of information via the network. The given below are the procedures on how to emulate the social network and perform basic social network analysis in OMNeT++ using the INET framework:
Step-by-Step Implementation:
- Set up OMNeT++ and INET Framework
- Install OMNeT++: Make sure that OMNeT++ is installed and configured on system.
- Install INET Framework: Download and install the INET framework that provides models for networking and mobility, and can be adapted for social network simulations.
- Define the Social Network Topology
Generate a network topology where nodes signify the individuals in a social network and their connections among nodes denote the social relationships or communication paths.
Example NED File (SocialNetwork.ned):
package mynetwork;
import inet.node.inet.StandardHost;
import inet.node.inet.Router;
network SocialNetwork
{
parameters:
int numNodes = default(5); // Number of nodes in the network
submodules:
node[numNodes]: StandardHost {
@display(“p=100,100;is=square,red”);
}
router: Router {
@display(“p=300,200”);
}
connections allowunconnected:
for i = 0..numNodes-1 {
node[i].ethg++ <–> ethernetLine <–> router.ethg++;
}
}
In this example:
- node[]: It denoted individuals or entities in the social network.
- router: Acts as a central router to facilitate interaction among nodes.
- Create a Social Network Interaction Protocol
We can generate a custom protocol that mimic the communication among nodes, such as messaging, information exchange, or relationship establishment. This protocol can gather information on these interactions for later analysis.
Example: Social Interaction Protocol (SocialInteractionProtocol.ned)
package mynetwork;
import inet.applications.base.ApplicationBase;
simple SocialInteractionProtocol extends ApplicationBase
{
gates:
input upperLayerIn;
output upperLayerOut;
input lowerLayerIn;
output lowerLayerOut;
}
SocialInteractionProtocol.cc (Basic Implementation)
#include “inet/common/INETDefs.h”
#include “inet/applications/base/ApplicationBase.h”
#include <map>
Define_Module(SocialInteractionProtocol);
void SocialInteractionProtocol::initialize(int stage) {
ApplicationBase::initialize(stage);
if (stage == INITSTAGE_LOCAL) {
interactionInterval = par(“interactionInterval”).doubleValue();
interactionTimer = new cMessage(“interactionTimer”);
scheduleAt(simTime() + interactionInterval, interactionTimer);
// Initialize interaction counters
interactionCounts.clear();
}
}
void SocialInteractionProtocol::handleMessageWhenUp(cMessage *msg) {
if (msg == interactionTimer) {
initiateInteraction();
scheduleAt(simTime() + interactionInterval, interactionTimer);
} else if (msg->getArrivalGate() == lowerLayerIn) {
handleInteraction(msg);
}
}
void SocialInteractionProtocol::initiateInteraction() {
// Simulate an interaction with a randomly chosen peer
int targetNode = intuniform(0, getParentModule()->getVectorSize() – 1);
if (targetNode != getParentModule()->getIndex()) {
cMessage *interactionMsg = new cMessage(“InteractionMessage”);
interactionMsg->addPar(“source”) = getParentModule()->getIndex();
interactionMsg->addPar(“target”) = targetNode;
sendDirect(interactionMsg, getParentModule()->getSubmodule(“node”, targetNode), “upperLayerIn”);
recordInteraction(getParentModule()->getIndex(), targetNode);
}
}
void SocialInteractionProtocol::handleInteraction(cMessage *msg) {
int sourceNode = msg->par(“source”);
int targetNode = msg->par(“target”);
// Record the interaction
recordInteraction(sourceNode, getParentModule()->getIndex());
EV << “Node ” << getParentModule()->getIndex() << ” interacted with Node ” << sourceNode << “\n”;
delete msg;
}
void SocialInteractionProtocol::recordInteraction(int source, int target) {
std::pair<int, int> interaction = std::make_pair(source, target);
if (interactionCounts.find(interaction) == interactionCounts.end()) {
interactionCounts[interaction] = 1;
} else {
interactionCounts[interaction]++;
}
}
void SocialInteractionProtocol::finish() {
// Output the interaction data for analysis
EV << “Final Interaction Counts:\n”;
for (const auto &entry : interactionCounts) {
EV << “Interaction between Node ” << entry.first.first << ” and Node ” << entry.first.second
<< “: ” << entry.second << ” times\n”;
}
cancelAndDelete(interactionTimer);
}
In this example:
- interactionInterval: Controls the interval at which a node starts an communication.
- initiateInteraction(): Randomly choose a peer to communication with and sends a message.
- handleInteraction(): To manage the incoming communication messages from other nodes.
- recordInteraction(): Keeps track of how usually each pair of nodes communicates.
- Configure the Simulation
Setup the simulation in the omnetpp.ini file to use custom social interaction protocol.
Example Configuration in omnetpp.ini:
network = SocialNetwork
**.node[*].applications[0].typename = “SocialInteractionProtocol”
**.node[*].applications[0].interactionInterval = 5s
- Run the Simulation
Run the simulation and monitor how nodes communicate over time. The communication will be recorded, and the information can be used to evaluate the social network structure.
- Analyse Social Network Interactions
After running the simulation, we can evaluate the communication data collected by the protocol. Some common social network analysis tasks include:
- Centrality Analysis: Regulate which nodes are the most central based on their interaction patterns.
- Community Detection: Classify the clusters or communities of nodes that communicate frequently with each other.
- Network Density: evaluate how densely connected the network is.
We can export the communication information for analysis using tools such as Python (with libraries like NetworkX) or R.
Example: Exporting Data for Centrality Analysis
void SocialInteractionProtocol::finish() {
std::ofstream outfile;
outfile.open(“interactions.csv”);
outfile << “Source,Target,Count\n”;
for (const auto &entry : interactionCounts) {
outfile << entry.first.first << “,” << entry.first.second << “,” << entry.second << “\n”;
}
outfile.close();
EV << “Interaction data exported to interactions.csv\n”;
cancelAndDelete(interactionTimer);
}
- Extend the Social Interaction Protocol
We can expand the simple social interaction protocol with more advanced features, such as:
- Weighted Interactions: Assign weights to interactions based on the type or frequency of communication.
- Temporal Analysis: Assess how the network structure changes over time by considering the timing of interactions.
- Trust and Reputation Systems: To mimic trust or reputation between nodes based on their interaction history.
- Document and Report Findings
After completing the simulations, document the social network analysis strategies validated, the outcome is obtained, and any optimizations made. This will help to familiarize the dynamics and structure of the social network being mimicked.
In this end, we clearly had idea on how to implement and validate the performance for social network analysis in the network nodes using the tool of OMNeT++. Further specific details regarding the social analysis is also provided.
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