How to Implement Scalable Parameterization in OMNeT++
To implement scalable parameterization in OMNeT++ has encompasses to setup the simulation in a way that permits to easily scale the number of nodes, network size, traffic patterns, or other parameters and this is helpful for running the large-scale simulations or discovering how various configurations impact the network performance. The given below are the brief procedures to implement the scalable parameterization in OMNeT++:
Step-by-Step Guide to Implementing Scalable Parameterization in OMNeT++
Step 1: Define a Scalable Network Topology
Plan network topology so that it can scale with the number of nodes or other parameters and need to use parameters in NED files to regulate the number of nodes, the structure of the network, and other context.
Example: Scalable Network Topology Definition
network ScalableNetwork
{
parameters:
int numNodes = default(10); // Number of nodes in the network
double gridSpacing = default(100); // Spacing between nodes in the grid
submodules:
nodes[numNodes]: StandardHost {
@display(“p=0,0”);
}
connections allowunconnected:
for i=0..numNodes-2 {
nodes[i].pppg++ <–> EthernetCable <–> nodes[i+1].pppg++;
}
}
In this sample, the numNodes parameter regulates the number of nodes in the network, and gridSpacing can be used to modify the physical layout of the nodes.
Step 2: Use .ini File for Parameter Configuration
Use the .ini file to set parameters that scale with simulation. This permits to easily adjust the size of the network, the amount of traffic, and other context without fluctuating the NED files.
Example .ini File Configuration
network = ScalableNetwork
sim-time-limit = 100s
# Scaling parameters
numRuns = 3 # Number of different runs with different scaling
repeat = ${numRuns}
# Example of scaling the number of nodes
*.numNodes = ${scalingFactor=1..3} * 10 # Scales from 10 to 30 nodes
# Example of scaling the spacing between nodes
*.gridSpacing = 100m
# Example of scaling traffic generation
*.nodes[*].app[0].sendInterval = 1s/${scalingFactor} # Faster transmission with more nodes
In this instance, scalingFactor is used to execute the simulation with 10, 20, and 30 nodes by adjusting the numNodes. The sendInterval parameter is accustomed based on the number of nodes to create more traffic as the network scales up.
Step 3: Configure Traffic Generation to Scale with the Network
We can also scale traffic patterns in the network by parameterizing traffic generation, like the interval among the packets or the size of the data being sent.
Example Traffic Generation Configuration
# Scaling traffic generation with the number of nodes
*.nodes[*].app[0].messageLength = ${scalingFactor} * 100B # Increase message size with scaling
*.nodes[*].app[0].sendInterval = 1s/${scalingFactor} # Decrease interval with scaling
This configuration upsurge the message length and drops the send interval as the number of nodes increases that generates a more intense traffic load on the network.
Step 4: Run Batch Simulations
OMNeT++ permits to run batch simulations where multiple configurations are validated in a single run. This is especially helpful for scaling studies.
Example Command to Run Batch Simulations
opp_runall -j4 ./scalable_sim -r 0..2
This command executes the simulation for each of the three scaling configurations (scalingFactor=1, 2, 3) in parallel using 4 CPU cores (-j4).
Step 5: Analyse the Results
To analyse the outcomes of scalable simulation to use the OMNeT++’s built-in tools. Look for trends as the network scales up, like changes in latency, throughput, or packet loss.
Example Analysis using Scave Tool
scavetool vector -p ‘name(“endToEndDelay:mean”)’ -F CSV-R results/*.vec > delay.csv
This command extracts the mean end-to-end delay from the outcomes of all runs and exports it to a CSV file for further analysis.
Step 6: Use Parameter Studies
OMNeT++ permits to set up parameter studies directly in the .ini file to thoroughly discover the impacts of numerous parameters.
Example Parameter Study in .ini File
[Config ScalingStudy]
network = ScalableNetwork
sim-time-limit = 100s
# Parameter study for scaling number of nodes
*.numNodes = ${scalingFactor=1..10} * 10
# Traffic parameters
*.nodes[*].app[0].sendInterval = uniform(0.5, 2) / ${scalingFactor} # Scales with number of nodes
This configuration sets up a parameter study where the number of nodes scales from 10 to 100 in steps of 10, and the send interval is accustomed consequently.
At the end, we thorough the manual and provide the valuable insights regarding how to implement the scalable parameterization in OMNeT++ tool. Further details regarding the implementation of the scalable parameterization in diverse simulations will be provided.
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