How to Implement Network Monitoring in OMNeT++
To implement network monitoring in OMNeT++ has needs to configure the mechanisms to observe, collect, and evaluate data about the network’s operation in real-time or during a simulation. The network monitoring usually concentrates on collecting parameters like bandwidth usage, packet loss, latency, and other key performance indicators (KPIs). The given below are the procedures to implement the network monitoring in OMNeT++:
Step-by-step Implementation:
- Set up OMNeT++ and INET Framework
- Make sure OMNeT++ and the INET framework are installed and properly configured.
- Generate a new project in OMNeT++ and has contain the INET framework where it delivers the several network models and tools for monitoring.
- Design the Network Topology
- Describe the network topology in an .ned file and this topology should conclude the nodes (e.g., routers, switches, hosts) that want to monitor.
Example .ned file:
network MonitoringNetwork {
submodules:
router1: Router {
@display(“p=100,100”);
}
router2: Router {
@display(“p=300,100”);
}
host1: StandardHost {
@display(“p=50,200”);
}
host2: StandardHost {
@display(“p=350,200”);
}
connections:
router1.pppg++ <–> Ethernet10G <–> router2.pppg++;
host1.ethg++ <–> Ethernet100M <–> router1.pppg++;
host2.ethg++ <–> Ethernet100M <–> router2.pppg++;
}
This sample configures a simple network with two routers and two hosts interconnected via the Ethernet links.
- Implement Monitoring Agents
- Execute monitoring agents on the nodes to monitor. These agents will gather the data on numerous parameters like bandwidth usage, packet loss, latency, and jitter.
Example of a simple monitoring agent:
class MonitoringAgent : public cSimpleModule
{
protected:
virtual void initialize() override;
virtual void handleMessage(cMessage *msg) override;
void collectMetrics();
};
void MonitoringAgent::initialize()
{
scheduleAt(simTime() + 1, new cMessage(“collectMetrics”));
}
void MonitoringAgent::handleMessage(cMessage *msg)
{
if (strcmp(msg->getName(), “collectMetrics”) == 0) {
collectMetrics();
scheduleAt(simTime() + 1, msg); // Collect metrics every second
}
}
void MonitoringAgent::collectMetrics()
{
// Example: Collect and log the number of packets received
int numReceived = gate(“in”)->getIncomingTransmissionQueue()->getLength();
EV << “Number of packets received: ” << numReceived << endl;
}
This agent intermittently collects and logs network metrics like the number of packets received.
- Configure Monitoring in the Simulation
- Configure the monitoring agents and other monitoring-related settings in the .ini file.
Example .ini file:
network = MonitoringNetwork
sim-time-limit = 100s
*.router1.numApps = 1
*.router1.app[0].typename = “MonitoringAgent”
*.router2.numApps = 1
*.router2.app[0].typename = “MonitoringAgent”
*.host1.numApps = 1
*.host1.app[0].typename = “MonitoringAgent”
*.host2.numApps = 1
*.host2.app[0].typename = “MonitoringAgent”
This configuration executes the monitoring agent on each node, collecting metrics throughout the simulation.
- Enable Scalar and Vector Recording
- OMNeT++ permits to record scalar (single value) and vector (time series) data that enable these recordings for the metrics that are interested in.
Example .ini file entries for recording metrics:
**.scalar-recording = true
**.vector-recording = true
# Record packet delay and throughput
**.scalar-recording-for = “delay throughput packetLoss”
**.vector-recording-for = “packetReceived”
This configuration will record delay, throughput, and packet loss as scalar metrics and the number of packets received as a vector metric.
- Run the Simulation
- Implement the simulation in OMNeT++ to collect monitoring data. OMNeT++ will make output files that containing the recorded metrics.
- To monitor real-time metrics or review logs to make sure that monitoring agents are properly capturing the desired data use OMNeT++’s graphical tools.
- Analyse the Collected Data
- After the simulation, measure the collected data from the scalar (.sca) and vector (.vec) files. OMNeT++ delivers the tools within its IDE to visualize and measure these metrics.
- We can also export the data to external tools such as MATLAB, Python, or Excel for further analysis and visualization.
Example analysis in Python:
import pandas as pd
import matplotlib.pyplot as plt
# Load vector data from OMNeT++ .vec file
data = pd.read_csv(‘results/MonitoringNetwork.vec’, delimiter=’\t’)
# Filter for packetReceived metrics
packet_data = data[data[‘name’].str.contains(‘packetReceived’)]
# Plot the number of packets received over time
plt.plot(packet_data[‘time’], packet_data[‘value’])
plt.xlabel(‘Time (s)’)
plt.ylabel(‘Packets Received’)
plt.title(‘Packet Reception Over Time’)
plt.show()
- Optimization and Refinement
- Based on the analysis, refine network configuration or the monitoring agents and it contains to adapt sampling rates, adding new metrics, or modifying the network topology.
- Test with numerous scenarios, like changing traffic loads or establishing network failures, to monitor how this impact network performance.
- Extend the Monitoring System
- Expand the monitoring system by integrating more sophisticated metrics, like Quality of Service (QoS) parameters, error rates, and traffic patterns.
- Execute additional features like alerting mechanisms in which the monitoring agent influence an alert when the particular thresholds are exceeded.
- Deliberate using a centralized monitoring technique where a dedicated node gathers and aggregates data from all other nodes in the network.
In the above setup are the complete procedures on how to setup the simulation and how to execute the network monitoring in OMNeT++ simulator. We plan to elaborate additional information about how the network monitoring will perform in other simulation tool.
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