To implement the Network Burst Loss Probability in ns3, we have to simulate a network that has the possibility of burst loss occurrences when the network is congested or other factors. If we want to accomplish the network, we have to use an error model which simulates burst losses within the network.
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In this following below, we are offering the step-by-step process to create a basic simulation of a network with burst loss probability in ns3.
Step-by-Step Implementation:
Step 1: Setup ns3 Environment
Ensure you have ns3 installed and properly configured.
git clone https://gitlab.com/nsnam/ns-3-dev.git
cd ns-3-dev
./waf configure
./waf build
Step 2: Create the Burst Loss Probability Simulation Script
We will create a script that sets up a network topology, configures point-to-point links, and simulates data transmission between the nodes. Burst losses can be introduced by an error models. Below, we provide an example on how to implement them.
#include “ns3/core-module.h”
#include “ns3/network-module.h”
#include “ns3/internet-module.h”
#include “ns3/point-to-point-module.h”
#include “ns3/applications-module.h”
#include “ns3/flow-monitor-module.h”
#include “ns3/error-model.h”
using namespace ns3;
NS_LOG_COMPONENT_DEFINE(“BurstLossExample”);
class BurstErrorModel : public ErrorModel
{
public:
static TypeId GetTypeId(void)
{
static TypeId tid = TypeId(“ns3::BurstErrorModel”)
.SetParent<ErrorModel>()
.SetGroupName(“Network”)
.AddConstructor<BurstErrorModel>()
.AddAttribute(“BurstSize”,
“The average size of a burst loss.”,
UintegerValue(5),
MakeUintegerAccessor(&BurstErrorModel::m_burstSize),
MakeUintegerChecker<uint32_t>())
.AddAttribute(“BurstInterval”,
“The average interval between bursts.”,
UintegerValue(50),
MakeUintegerAccessor(&BurstErrorModel::m_burstInterval),
MakeUintegerChecker<uint32_t>());
return tid;
}
BurstErrorModel()
: m_burstSize(5),
m_burstInterval(50),
m_burstCounter(0),
m_packetCounter(0)
{
}
private:
virtual bool DoCorrupt(Ptr<Packet> p)
{
m_packetCounter++;
if (m_packetCounter % m_burstInterval == 0)
{
m_burstCounter = m_burstSize;
}
if (m_burstCounter > 0)
{
m_burstCounter–;
return true;
}
return false;
}
virtual void DoReset(void)
{
m_burstCounter = 0;
m_packetCounter = 0;
}
uint32_t m_burstSize;
uint32_t m_burstInterval;
uint32_t m_burstCounter;
uint32_t m_packetCounter;
};
int main(int argc, char *argv[])
{
CommandLine cmd;
cmd.Parse(argc, argv);
// Create nodes
NodeContainer nodes;
nodes.Create(4); // Four nodes for a simple network topology
// Set up point-to-point links
PointToPointHelper p2p;
p2p.SetDeviceAttribute(“DataRate”, StringValue(“5Mbps”));
p2p.SetChannelAttribute(“Delay”, StringValue(“2ms”));
// Install point-to-point devices and channels between nodes
NetDeviceContainer devices;
devices = p2p.Install(nodes.Get(0), nodes.Get(1));
devices.Add(p2p.Install(nodes.Get(1), nodes.Get(2)));
devices.Add(p2p.Install(nodes.Get(2), nodes.Get(3)));
// Add burst error model to the devices
Ptr<BurstErrorModel> bem = CreateObject<BurstErrorModel>();
devices.Get(1)->SetAttribute(“ReceiveErrorModel”, PointerValue(bem));
devices.Get(2)->SetAttribute(“ReceiveErrorModel”, PointerValue(bem));
// Install the internet stack
InternetStackHelper stack;
stack.Install(nodes);
// Assign IP addresses
Ipv4AddressHelper address;
address.SetBase(“10.1.1.0”, “255.255.255.0”);
Ipv4InterfaceContainer interfaces = address.Assign(devices);
// Set up routing
Ipv4GlobalRoutingHelper::PopulateRoutingTables();
// Install applications to generate traffic
uint16_t port = 9;
// Node 0 will send data to Node 3
OnOffHelper onoff(“ns3::UdpSocketFactory”, Address(InetSocketAddress(interfaces.GetAddress(3), port)));
onoff.SetConstantRate(DataRate(“1Mbps”));
ApplicationContainer apps = onoff.Install(nodes.Get(0));
apps.Start(Seconds(1.0));
apps.Stop(Seconds(10.0));
// Install packet sink on Node 3 to receive packets
PacketSinkHelper sink(“ns3::UdpSocketFactory”, Address(InetSocketAddress(Ipv4Address::GetAny(), port)));
apps = sink.Install(nodes.Get(3));
apps.Start(Seconds(0.0));
apps.Stop(Seconds(10.0));
// Enable FlowMonitor to measure performance metrics
FlowMonitorHelper flowmon;
Ptr<FlowMonitor> monitor = flowmon.InstallAll();
// Run the simulation
Simulator::Stop(Seconds(10.0));
Simulator::Run();
// Print per-flow statistics
monitor->CheckForLostPackets();
Ptr<Ipv4FlowClassifier> classifier = DynamicCast<Ipv4FlowClassifier>(flowmon.GetClassifier());
std::map<FlowId, FlowMonitor::FlowStats> stats = monitor->GetFlowStats();
for (std::map<FlowId, FlowMonitor::FlowStats>::const_iterator i = stats.begin(); i != stats.end(); ++i)
{
Ipv4FlowClassifier::FiveTuple t = classifier->FindFlow(i->first);
NS_LOG_UNCOND(“Flow ” << i->first << ” (” << t.sourceAddress << ” -> ” << t.destinationAddress << “)”);
NS_LOG_UNCOND(” Tx Packets: ” << i->second.txPackets);
NS_LOG_UNCOND(” Tx Bytes: ” << i->second.txBytes);
NS_LOG_UNCOND(” Rx Packets: ” << i->second.rxPackets);
NS_LOG_UNCOND(” Rx Bytes: ” << i->second.rxBytes);
NS_LOG_UNCOND(” Lost Packets: ” << i->second.lostPackets);
NS_LOG_UNCOND(” Throughput: ” << i->second.rxBytes * 8.0 / (i->second.timeLastRxPacket.GetSeconds() – i->second.timeFirstTxPacket.GetSeconds()) / 1024 / 1024 << ” Mbps”);
}
// Clean up
Simulator::Destroy();
return 0;
}
Step 3: Compile and Run the Simulation
- Compile the Simulation:
./waf configure –enable-examples
./waf build
Run the Simulation:
./waf –run scratch/burst-loss-example
Step 4: Analyze Results
In the above example, we are simulating the script that setting up a network topology with the help of error model which introduces the burst losses. We use FlowMonitor to aggregate and print out statistics about the traffic flows, such as packet loss, throughput, and delay.
Additional Considerations
If want to optimize the network burst loss probability we can also extends its functionalities. Here’s the following steps to consider:
1. Complex Topologies
We have to simulate the real-world networks to create more complex network topologies such as mesh, star, and ring topologies.
2. Dynamic Routing Protocols
We have to manage the routing packets in the network and habitually find their optimal path by integrating the routing protocols includes OSPF, BGP or AODV.
3. Traffic Patterns
To read their impact on the network, we are simulating different types of traffic patterns like IoT data, VoIP, video streaming, and bulk data transfer.
4. Quality of Service (QoS)
We are prioritizing certain types of traffic and ensuring that critical data flows receive the necessary bandwidth and low latency by implementing QoS mechanism.
5. Performance Metrics
We have to accumulate and analyze the added metrics like jitter, packet delay variation and error rates that helps to evaluate the network performance more comprehensively.
As we discussed earlier, we understand the implementation process and additional techniques of Network Burst Loss Probability in ns3 tool. We also provide further information or materials about the Burst Loss and its network, if needed.
