Ns3 Projects for B.E/B.Tech M.E/M.Tech PhD Scholars.  Phone-Number:9790238391   E-mail: ns3simulation@gmail.com

How to Implement M2M satellite communication in ns3

To implement Machine-to-Machine (M2M) satellite communication in ns3, a network has to be simulated. In that network communication should be done with each other devices via a satellite. For setting up this, it is necessary to set-up nodes that represent the devices, a satellite node, configuring the communication links, and simulating data transmission between the devices via the satellite.

The following steps given below will guide on setting up M2M satellite communication in ns3.

Step-by-step guide to implement M2M satellite communication in ns3:

Step 1: Setup ns3 Environment

Ensure that ns3 is 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 M2M Satellite Communication Simulation Script

We will create a script that sets up devices, a satellite node, configures their mobility, and simulates data transmission between the devices via the satellite.

#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/mobility-module.h”

#include “ns3/flow-monitor-module.h”

using namespace ns3;

NS_LOG_COMPONENT_DEFINE(“M2MSatelliteCommunicationExample”);

int main(int argc, char *argv[])

{

CommandLine cmd;

cmd.Parse(argc, argv);

// Create ground devices

NodeContainer deviceNodes;

deviceNodes.Create(2); // Two M2M devices

// Create satellite node

NodeContainer satelliteNode;

satelliteNode.Create(1); // One satellite

// Set up point-to-point links for the ground-to-satellite communication

PointToPointHelper p2p;

p2p.SetDeviceAttribute(“DataRate”, StringValue(“1Gbps”));

p2p.SetChannelAttribute(“Delay”, StringValue(“300ms”)); // High delay for satellite communication

NetDeviceContainer groundDevicesToSatellite;

groundDevicesToSatellite = p2p.Install(deviceNodes.Get(0), satelliteNode.Get(0));

groundDevicesToSatellite.Add(p2p.Install(deviceNodes.Get(1), satelliteNode.Get(0)));

// Install the internet stack

InternetStackHelper stack;

stack.Install(deviceNodes);

stack.Install(satelliteNode);

// Assign IP addresses

Ipv4AddressHelper address;

address.SetBase(“10.1.1.0”, “255.255.255.0”);

Ipv4InterfaceContainer interfaces = address.Assign(groundDevicesToSatellite);

// Set up mobility model for the ground devices (fixed)

MobilityHelper mobility;

mobility.SetMobilityModel(“ns3::ConstantPositionMobilityModel”);

mobility.Install(deviceNodes)

// Set up mobility model for the satellite (fixed for simplicity)

mobility.Install(satelliteNode);

Ptr<ConstantPositionMobilityModel>posSatellite=satelliteNode.Get(0)->GetObject<ConstantPositionMobilityModel>();

posSatellite->SetPosition(Vector(0.0, 0.0, 35786.0)); // Geostationary orbit altitude

// Install applications to generate traffic

uint16_t port = 9;

// Device 0 will send data to Device 1 via the satellite

OnOffHelperonoff(“ns3::UdpSocketFactory”, Address(InetSocketAddress(interfaces.GetAddress(1), port)));

onoff.SetConstantRate(DataRate(“500Mbps”));

ApplicationContainer apps = onoff.Install(deviceNodes.Get(0));

apps.Start(Seconds(1.0));

apps.Stop(Seconds(10.0));

// Install packet sink on Device 1 to receive packets

PacketSinkHelpersink(“ns3::UdpSocketFactory”, Address(InetSocketAddress(Ipv4Address::GetAny(), port)));

apps = sink.Install(deviceNodes.Get(1));

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

  1. Compile the Simulation:

./waf configure –enable-examples

./waf build

Run the Simulation:

./waf –run scratch/m2m-satellite-communication-example

Step 4: Analyze Results

The simulation script sets up an M2M satellite network with two ground devices communicating via a satellite. FlowMonitor is used to collect and print out statistics about the traffic flows, such as packet loss, throughput, and delay.

Additional Considerations

To extend the functionality of your M2M satellite communication simulation, consider the following:

1. Advanced Mobility Models

Implement more realistic mobility models to simulate the movement of satellites and devices, including LEO, MEO, and GEO satellites.

2. Dynamic Routing

Integrate dynamic routing protocols to manage the changing topology of a satellite network as satellites move.

3. Fault Tolerance

Implement fault tolerance mechanisms to handle link failures and satellite outages, ensuring continuous communication.

4. Traffic Patterns

Simulate different types of traffic patterns, such as IoT data, VoIP, video streaming, and bulk data transfer, to study their impact on the network.

5. Quality of Service (QoS)

Implement QoS mechanisms to prioritize certain types of traffic and ensure that critical data flows receive the necessary bandwidth and low latency.

6. Performance Metrics

Collect and analyze additional metrics such as jitter, packet delay variation, and error rates to evaluate the network performance more comprehensively.

Over all, we had elaborately explained about the terms and steps involved in implementing M2M satellite communication in ns3 by setting up the environment, creating simulation script, compile and running the simulation and last analyzing the results using flowmonitor.

We have extensive experience in M2M satellite communication within the ns3tool platform. Feel free to reach out to us for further guidance. Our team provides  networking comparison analysis and delivers the best simulation results.