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How to Calculate Network Queue time in omnet++

To calculate the network queue time in OMNeT++ has contain to evaluate the time a packet devotes in a queue at a network node  that has to include a router, switch, or any other device before being processed or forwarded. The Queue time is significant parameters for considerate the network performance, particular in terms of latency and congestion.

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The below are the procedures of how you can calculate the network queue time in OMNeT++:

Step-by-Step Implementation:

  1. Set up the Queue

Make sure network node module has a queue implemented and this queue holds packets before they are processed or forwarded. OMNeT++ delivers the numerous queue modules like cQueue, PassiveQueue, DropTailQueue that can use or extend.

Example: Setting up a Simple Queue

cQueue packetQueue;  // A queue to hold packets

  1. Track the Arrival Time of Packets

When a packet reaches at the queue, record its arrival time. This is significant for estimating the time the packet spends in the queue.

Example: Recording Packet Arrival Time

class Node : public cSimpleModule {

private:

cQueue packetQueue;

std::map<cMessage*, simtime_t> arrivalTimes;  // Map to store packet arrival times

protected:

virtual void initialize() override {

packetQueue.setName(“packetQueue”);

}

virtual void handleMessage(cMessage *msg) override {

if (msg->isSelfMessage()) {

// Process the message if it’s not a packet (e.g., a timer)

processPacket(msg);

} else {

// Record the arrival time of the packet

arrivalTimes[msg] = simTime();

packetQueue.insert(msg);

// Schedule the packet for processing (depending on your logic)

scheduleAt(simTime() + 0.01, msg);  // Example processing delay

}

}

};

  1. Calculate the Queue Time

When a packet is dequeued for processing or forwarding, compute its queue time by subtracting its arrival time from the current simulation time.

Example: Calculating Queue Time

void processPacket(cMessage *msg) {

// Retrieve the packet from the queue

cMessage *packet = (cMessage*)packetQueue.pop();

// Calculate the time spent in the queue

simtime_t arrivalTime = arrivalTimes[packet];

simtime_t queueTime = simTime() – arrivalTime;

EV << “Packet spent ” << queueTime << ” seconds in the queue.” << endl;

recordScalar(“Queue Time”, queueTime);

// Remove the arrival time entry

arrivalTimes.erase(packet);

// Further processing or forwarding of the packet

send(packet, “out”);

}

  1. Record and Emit Queue Time

We need to record the calculated queue time as a scalar or emit it as a signal for analysis.

simsignal_t queueTimeSignal;

void initialize() override {

queueTimeSignal = registerSignal(“queueTime”);

}

void processPacket(cMessage *msg) {

cMessage *packet = (cMessage*)packetQueue.pop();

simtime_t arrivalTime = arrivalTimes[packet];

simtime_t queueTime = simTime() – arrivalTime;

EV << “Packet spent ” << queueTime << ” seconds in the queue.” << endl;

emit(queueTimeSignal, queueTime);

recordScalar(“Queue Time”, queueTime);

arrivalTimes.erase(packet);

send(packet, “out”);

}

  1. Run the Simulation

Run OMNeT++ simulation to gather data on queue times across several network nodes.

  1. Analyse the Results

After the simulation, we need to use OMNeT++’s analysis tools or export the information for further analysis. Key analysis points might include:

  • Average Queue Time: The mean time packets spend in the queue.
  • Queue Time Distribution: Understanding how queue times vary across packets.
  • Maximum Queue Time: Identifying potential bottlenecks where packets experience excessive delays.
  1. Example Scenario

The below is the more complete example that incorporate the above steps into an OMNeT++ module:

class Node : public cSimpleModule {

private:

cQueue packetQueue;

std::map<cMessage*, simtime_t> arrivalTimes;

simsignal_t queueTimeSignal;

protected:

virtual void initialize() override {

packetQueue.setName(“packetQueue”);

queueTimeSignal = registerSignal(“queueTime”);

}

virtual void handleMessage(cMessage *msg) override {

if (msg->isSelfMessage()) {

processPacket(msg);

} else {

arrivalTimes[msg] = simTime();

packetQueue.insert(msg);

// Example: process the packet after a small delay

scheduleAt(simTime() + 0.01, new cMessage(“processPacket”));

}

}

void processPacket(cMessage *msg) {

if (!packetQueue.isEmpty()) {

cMessage *packet = (cMessage*)packetQueue.pop();

simtime_t arrivalTime = arrivalTimes[packet];

simtime_t queueTime = simTime() – arrivalTime;

EV << “Packet spent ” << queueTime << ” seconds in the queue.” << endl;

emit(queueTimeSignal, queueTime);

recordScalar(“Queue Time”, queueTime);

arrivalTimes.erase(packet);

send(packet, “out”);

}

delete msg;  // Clean up the self-message

}

};

  1. Post-Simulation Analysis

After completing the simulation, measure the recorded queue times to evaluate the performance of the network. High average queue times signify congestion or inefficiencies in the network that could be addressed by enhancing routing, load balancing, or resource allocation.

From this page, we had learned and get the knowledge on how to measure the queue times in the network to handle the enhanced routing, load balancing using the OMNeT++.  We deliver the additional information on how the network queue time will perform in other simulation time.

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