How to Calculate Network Burstiness in omnet++
To calculate the network burstiness in OMNeT++, we have to assess the variability of the traffic over time. To showcase the short periods of high activity (bursts) followed by periods of low activity or inactivity, the burstiness refers to the tendency of the traffic. Burstiness can expressively impact network performance because during high-activity periods it can lead to congestion and packet loss. In the below, we offered the process to calculate network burstiness:
Steps to Calculate Network Burstiness in OMNeT++:
- Define Burstiness Metric:
- Inter-Arrival Time Variability: The variation in time amongst sequential packet arrivals.
- Peak-to-Average Ratio: The ratio of the highest traffic rate to the average traffic rate over a period.
- Coefficient of Variation (CV): The ratio of the standard deviation of packet arrival times to the mean packet arrival time.
- Set Up the Network Model:
- State the network topology using NED files in OMNeT++. Generate nodes, links, and any relevant traffic generation applications. The traffic pattern should exhibit variability which permits for burstiness analysis.
- Generate Traffic:
- Create traffic with variable rates using traffic generators like UdpApp or TcpApp. In the network, this variability is essential to monitor bursty behavior in the network.
- Track Packet Arrival Times:
- Track the arrival times of packets at a certain node or through the network. By recording the time difference amongst consecutive packet arrivals, we can compute the inter-arrival times.
- Calculate Burstiness:
- Inter-Arrival Time Analysis: Inter-Arrival Time=Arrival Timen−Arrival Timen−1\text{Inter-Arrival Time} = \text{Arrival Time}_n – \text{Arrival Time}_{n-1}Inter-Arrival Time=Arrival Timen−Arrival Timen−1
- Peak-to-Average Ratio: Peak-to-Average Ratio=Peak Traffic RateAverage Traffic Rate\text{Peak-to-Average Ratio} = \frac{\text{Peak Traffic Rate}}{\text{Average Traffic Rate}}Peak-to-Average Ratio=Average Traffic RatePeak Traffic Rate
- Coefficient of Variation (CV): CV=Standard Deviation of Inter-Arrival TimesMean Inter-Arrival Time\text{CV} = \frac{\text{Standard Deviation of Inter-Arrival Times}}{\text{Mean Inter-Arrival Time}}CV=Mean Inter-Arrival TimeStandard Deviation of Inter-Arrival Times
Example Implementation: Calculating Inter-Arrival Time Variability
Follow the sample to calculate the Inter-arrival time variability:
#include <omnetpp.h>
#include <vector>
#include <numeric>
#include <cmath>
using namespace omnetpp;
class BurstinessModule : public cSimpleModule {
private:
std::vector<simtime_t> arrivalTimes; // Store arrival times of packets
simsignal_t cvSignal; // Signal to record the coefficient of variation
protected:
virtual void initialize() override {
cvSignal = registerSignal(“cvSignal”);
}
virtual void handleMessage(cMessage *msg) override {
// Record the arrival time of each packet
simtime_t arrivalTime = simTime();
arrivalTimes.push_back(arrivalTime);
// Calculate inter-arrival times if there are at least two packets
if (arrivalTimes.size() > 1) {
std::vector<double> interArrivalTimes;
for (size_t i = 1; i < arrivalTimes.size(); ++i) {
double interArrivalTime = (arrivalTimes[i] – arrivalTimes[i – 1]).dbl();
interArrivalTimes.push_back(interArrivalTime);
}
// Calculate mean of inter-arrival times
double mean = std::accumulate(interArrivalTimes.begin(), interArrivalTimes.end(), 0.0) / interArrivalTimes.size();
// Calculate standard deviation of inter-arrival times
double sq_sum = std::inner_product(interArrivalTimes.begin(), interArrivalTimes.end(), interArrivalTimes.begin(), 0.0);
double stdev = std::sqrt(sq_sum / interArrivalTimes.size() – mean * mean);
// Calculate coefficient of variation (CV)
double cv = (mean > 0) ? stdev / mean : 0.0;
// Emit the CV signal
emit(cvSignal, cv);
EV << “Coefficient of Variation (CV) of Inter-Arrival Times: ” << cv << “\n”;
}
// Process the received packet
delete msg;
}
};
Define_Module(BurstinessModule);
Explanation:
- BurstinessModule:
- arrivalTimes: A vector to store the arrival times of packets. Using this data, we can estimate the inter-arrival times.
- cvSignal: Registers a signal to emanate the coefficient of variation (CV) of inter-arrival times.
- handleMessage() Function:
- Records the arrival time of every packet.
- When at least two packets have been received, computes the inter-arrival times.
- Computes the mean and standard deviation of the inter-arrival times.
- Calculates the coefficient of variation (CV) as the ratio of the standard deviation to the mean inter-arrival time.
- Emits the CV as a signal for analysis, which serves as a calculate of burstiness.
- Run the Simulation:
- Compile and run the OMNeT++ project. The simulation will track packet arrivals and compute the CV of inter-arrival times, offering an indication of the burstiness of the network.
- Analyze and Interpret Results:
- In traffic, higher CV signifies higher burstiness, means there is more variability in packet arrivals. This could lead to periods of high traffic (bursts) followed by periods of low traffic.
- Evaluate how burstiness impacts network performance like increased packet loss or delays during bursts.
Additional Considerations:
- Traffic Patterns: To monitor the burstiness, the generated traffic should have variability. Experiment with various traffic patterns to see how they impact burstiness.
- Burst Mitigation: If burstiness is triggering performance issues, consider executing traffic shaping or congestion control mechanisms in the network model.
Finally, this demonstration is on how to calculate burstiness based on the coefficient of variation (CV) of inter-arrival times in OMNeT++ by providing an example. We will guide you, if you have any concerns regarding this process.
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