How to Start Least Cost Routing Projects Using OMNeT++
To start Least Cost Routing using OMNeT++ environment, we need to find the paths among the nodes, which reduce the total cost like delay, bandwidth usage, or energy consumption. Below is a sequential methodology to replicate and execute the Least Cost Routing in OMNeT++.
Steps to Start Least Cost Routing Project in OMNeT++
- Set Up the Environment
Install OMNeT++
- We should download the new version of OMNeT++ on the system.
- Adhere to the installation guidance and experiment the configuration including sample projects.
Install INET Framework
- We have to download the INET framework with OMNeT++ version.
- Construct the framework:
make makefiles
make
- Understand Least Cost Routing
Key Features
- Path cost is determined according to the predefined parameters such as:
- Bandwidth
- Latency
- Hop count
- Energy usage
- Algorithms utilised:
- Dijkstra’s Algorithm which is generally utilised to find shortest path or least cost.
- Bellman-Ford Algorithm is appropriate for distributed environments.
- Plan Your Simulation
Define Objectives
- Execute a least-cost routing algorithm.
- Replicate the performance parameters like:
- Convergence time.
- Routing overhead.
- Cost efficiency of routes.
Network Topology
- Choose the volume of nodes and its connectivity.
- Allocate weights (costs) to connects:
- Fixed costs: Predefined using .ned or .ini files.
- Dynamic costs: Differ the costs depends on network conditions like congestion.
- Create a New OMNeT++ Project
- Go to OMNeT++ IDE.
- Select File > New > OMNeT++ Project.
- Name it to the project such as LeastCostRouting and choose Finish.
- Implement Least Cost Routing
Extend or Create a Routing Module
- In the INET framework like inet::RoutingTable, prolong an existing routing module.
- Execute the Dijkstra’s algorithm for centralized routing or Bellman-Ford for distributed routing.
Example Implementation Using Dijkstra’s Algorithm
Make a custom routing module:
class LeastCostRouting : public cSimpleModule {
private:
std::map<int, double> linkCosts; // Link costs for neighbors
std::map<int, double> distanceVector; // Distance to all nodes
std::map<int, int> nextHop; // Next hop for each destination
protected:
virtual void initialize() override {
int nodeId = getId();
distanceVector[nodeId] = 0; // Cost to itself is 0
for (auto neighbor : getNeighbors()) {
distanceVector[neighbor] = INFINITY; // Initial cost to others
}
}
virtual void handleMessage(cMessage *msg) override {
auto packet = check_and_cast<RoutingPacket *>(msg);
updateRoutingTable(packet->getDistanceVector());
}
void updateRoutingTable(const std::map<int, double>& receivedVector) {
bool updated = false;
for (const auto& [destination, cost] : receivedVector) {
double newCost = cost + linkCosts[destination];
if (newCost < distanceVector[destination]) {
distanceVector[destination] = newCost;
nextHop[destination] = destination;
updated = true;
}
}
if (updated) {
broadcastDistanceVector();
}
}
void broadcastDistanceVector() {
for (int i = 0; i < gateSize(“out”); ++i) {
auto packet = new RoutingPacket();
packet->setDistanceVector(distanceVector);
send(packet, “out”, i);
}
}
};
- Define Network Topology
Create a .ned File
Make a network topology including nodes and link costs in a .ned file:
network LeastCostNetwork {
submodules:
node[10]: StandardHost {
parameters:
@display(“i=device/router”);
routingProtocol = “LeastCostRouting”;
}
connections:
node[0].pppg++ <–> { delay = 10ms; datarate = 10Mbps; cost = 5; } <–> node[1].pppg++;
node[1].pppg++ <–> { delay = 15ms; datarate = 5Mbps; cost = 10; } <–> node[2].pppg++;
}
- Configure the Simulation
Add Parameters in omnetpp.ini
Set the simulation metrics and link costs using .ini files:
[Config LeastCostSimulation]
network = LeastCostNetwork
*.node[*].routingProtocol = “LeastCostRouting”
*.node[*].initialEnergy = 100J
*.linkCost = uniform(1, 10) # Random link costs
simulation.timeLimit = 100s
- Run the Simulation
- Make use of Tkenv for envisioning the network and packet flow in OMNeT++ environment.
- Observe the convergence time, routing table updates, and packet delivery.
- Analyze Results
Evaluate Metrics
- Cost Efficiency:
- We need to equate the computed paths including theoretical least-cost paths.
- Convergence Time:
- Estimate the duration for every node to become stable its routing tables.
- Routing Overhead:
- Compute the volume of control messages that are swapped in routing.
Visualization
- Make use of OMNeT++’s built-in tools for:
- Envisioning network traffic.
- Recording routing table updates.
- Transfer outcomes into external tools like MATLAB or Python for further analysis.
- Extend and Optimize
Dynamic Cost Adjustments
- Mimic real-time changes within link costs according to the:
- Traffic congestion.
- Node energy levels.
Handle Failures
- Launch link or node failures for experiment the resilience of protocol.
Compare with Other Protocols
- We need to replicate and equate the least-cost routing including protocols such as OSPF or RIP.
Following these steps enable you to simulate and implement the Least Cost Routing projects using OMNeT++ environment and we can extend the project to investigate several features and more insights as required.
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