How to Calculate Network Mean Opinion Score in omnet++

To calculate the Network Mean Opinion Score (MOS) in OMNeT++ has needs to evaluate the perceived quality of a network service like voice or video transmission. The MOS is a particular parameter that rates the quality of the service on a scale usually from 1 (poor) to 5 (excellent). In simulation aspects like OMNeT++, MOS can be calculated based on objective network parameters like packet loss, latency, and jitter, which relate with user experience. The below is the brief structure to execute the MOS in OMNeT++:

Steps to Calculate MOS in OMNeT++

1. Define the Quality Metrics:
   • Select the network parameters that affect the quality of service (QoS). Common metrics include:
     • Packet Loss: The percentage of packets lost during transmission.
     • Latency: The time it takes for a packet to travel from the source to the destination.
     • Jitter: The variation in packet arrival times.
2. Mapping QoS Metrics to MOS:
   • There are realistic models that map these network performance parameters to MOS. For an instance, for VoIP (Voice over IP), the E-model is usually used to compute MOS.

A simplified method can includes the following formula:

MOS=1+4×(R−0)Rmax−0MOS = 1 + \frac{4 \times (R – 0)}{R_{\text{max}} – 0}MOS=1+Rmax​−04×(R−0)​

Where:

1. • RRR is the quality rating derived from network parameters.
   • RmaxR_{\text{max}}Rmax​ is the maximum possible quality rating (typically set to 100).

The quality rating RRR can be estimated as:

R=R0−Iloss−Idelay−IjitterR = R_0 – I_{loss} – I_{delay} – I_{jitter}R=R0​−Iloss​−Idelay​−Ijitter​

1. • R0R_0R0​ is the base quality rating (typically 94.2).
   • IlossI_{loss}Iloss​ is the impairment due to packet loss.
   • IdelayI_{delay}Idelay​ is the impairment due to latency.
   • IjitterI_{jitter}Ijitter​ is the impairment due to jitter.
2. Calculate Impairment Factors:
   • Impairment Due to Packet Loss (IlossI_{loss}Iloss​): Iloss=20×log⁡10(1+10×Packet Loss Percentage)I_{loss} = 20 \times \log_{10}(1 + 10 \times \text{Packet Loss Percentage})Iloss​=20×log10​(1+10×Packet Loss Percentage)
   • Impairment Due to Latency (IdelayI_{delay}Idelay​): Idelay=0.024×Latency+0.11×(Latency−177.3)×1(Latency>177.3)I_{delay} = 0.024 \times \text{Latency} + 0.11 \times (\text{Latency} – 177.3) \times \mathbb{1}(\text{Latency} > 177.3)Idelay​=0.024×Latency+0.11×(Latency−177.3)×1(Latency>177.3)
   • Impairment Due to Jitter (IjitterI_{jitter}Ijitter​):
     • Jitter can be encompassed as part of the delay impairment or designed separately based on comparable functions.
3. Implementing in OMNeT++:
   • Execute the MOS calculation in simulation model. Here is a simplified sample:

double packetLossPercentage; // Calculated during the simulation

double latency;              // Calculated during the simulation

double jitter;               // Calculated during the simulation

double R0 = 94.2; // Base quality rating

double Iloss, Idelay, Ijitter, R, MOS;

// Calculate impairment due to packet loss

Iloss = 20 * log10(1 + 10 * packetLossPercentage);

// Calculate impairment due to delay

Idelay = 0.024 * latency;

if (latency > 177.3) {

Idelay += 0.11 * (latency – 177.3);

}

// Optionally calculate impairment due to jitter separately

Ijitter = 0.01 * jitter; // Example factor

// Calculate the quality rating

R = R0 – Iloss – Idelay – Ijitter;

// Calculate MOS

MOS = 1 + 4 * (R – 0) / (100 – 0);

EV << “Mean Opinion Score (MOS): ” << MOS << endl;

1. Post-Simulation Analysis:
   • We need to record the MOS values over time or across several scenarios and measure how network conditions impact the perceived quality.
2. Interpreting the MOS Values:
   • A MOS of 4-5 is generally considered excellent.
   • A MOS of 3-4 is considered good.
   • A MOS of 2-3 is considered fair.
   • A MOS below 2 indicates poor quality.

Example Application

In a VoIP scenario, we can use the MOS to measure how several network configurations like different routing protocols, traffic loads can affect the user experience. By running multiple simulations with varying conditions we need to determine which configurations offer the preeminent user experience.

In this module, we had successfully calculate and implement the mean option score in the network using OMNeT++ and also we plan to elaborate on the Network Mean Opinion Score procedure in other simulation scenarios.

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