How to Start Wireless Body Area Network Projects Using NS3

To start a Wireless Body Area Network (WBAN) project using NS3, we want to contain configuring network sensor nodes, which interact in a small area then frequently around the human body, for data collection and analysis observing the health-related information and interact with a central sink such as a smartphone or gateway. WBANs are normally categorised using low-power, short-range interaction, and for low-power personal area networks, we can function at diverse protocols like IEEE 802.15.4.

Below, we mentioned a stepwise method to configuring a basic WBAN project in NS3.

Steps to Start Wireless Body Area Network Projects in NS3

  1. Install NS3
  1. Download and Install NS3:

git clone https://gitlab.com/nsnam/ns-3-dev.git ns-3

cd ns-3

./waf configure –enable-examples –enable-tests

./waf build

  1. Verify Installation by executing a simple instance like a WiFi or Zigbee (802.15.4) example, making sure that NS3 is properly functioning:

./waf –run=wifi-simple-adhoc

  1. Understand WBAN Components

We will normally operating in a WBAN project:

  • Sensor Nodes: Nodes, which gather the health-related data that frequently connected to or embedded within the body such as heart rate monitors, glucose sensors.
  • Sink Node (Gateway): From sensor nodes, accumulates data and transmits it to an external network or storage.
  • Communication Protocol: IEEE 802.15.4 is generally utilized within WBANs by reason of their low power consumption.
  • Mobility Models: Although WBANs are static around the body then basic mobility models can be replicated body movements.
  1. Set Up Basic WBAN Network Topology

A simple WBAN topology encompasses numerous sensor nodes, which send data to a central sink node. The sensor nodes utilize a low-power protocol such as 802.15.4 in WBANs that is optimal for short-range interaction.

Example: Basic WBAN with IEEE 802.15.4

Here’s an instance configures a WBAN including numerous sensor nodes utilizing the IEEE 802.15.4 standard to interact with a central sink node.

#include “ns3/core-module.h”

#include “ns3/network-module.h”

#include “ns3/internet-module.h”

#include “ns3/point-to-point-module.h”

#include “ns3/csma-module.h”

#include “ns3/applications-module.h”

#include “ns3/mobility-module.h”

#include “ns3/lr-wpan-module.h”

#include “ns3/sixlowpan-module.h”

using namespace ns3;

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

CommandLine cmd;

cmd.Parse(argc, argv);

// Create nodes for sensors and one sink node

NodeContainer sensorNodes;

sensorNodes.Create(4); // Four sensor nodes

NodeContainer sinkNode;

sinkNode.Create(1); // One sink node

// Configure 802.15.4 (LR-WPAN) devices

LrWpanHelper lrWpanHelper;

NetDeviceContainer sensorDevices = lrWpanHelper.Install(sensorNodes);

NetDeviceContainer sinkDevice = lrWpanHelper.Install(sinkNode);

lrWpanHelper.AssociateToPan(sensorDevices, 0); // Set up the WBAN PAN ID

// Install 6LoWPAN for IP-based communication over 802.15.4

SixLowPanHelper sixlowpanHelper;

NetDeviceContainer sensorSixlowpanDevices = sixlowpanHelper.Install(sensorDevices);

NetDeviceContainer sinkSixlowpanDevice = sixlowpanHelper.Install(sinkDevice);

// Install Internet stack for IP addressing

InternetStackHelper internet;

internet.Install(sensorNodes);

internet.Install(sinkNode);

// Assign IP addresses to devices

Ipv6AddressHelper ipv6;

ipv6.SetBase(Ipv6Address(“2001:1::”), Ipv6Prefix(64));

Ipv6InterfaceContainer sensorInterfaces = ipv6.Assign(sensorSixlowpanDevices);

Ipv6InterfaceContainer sinkInterface = ipv6.Assign(sinkSixlowpanDevice);

// Set up a mobility model for the WBAN nodes (stationary nodes with possible minor movement)

MobilityHelper mobility;

mobility.SetPositionAllocator(“ns3::GridPositionAllocator”,

“MinX”, DoubleValue(0.0),

“MinY”, DoubleValue(0.0),

“DeltaX”, DoubleValue(5.0),

“DeltaY”, DoubleValue(5.0),

“GridWidth”, UintegerValue(2),

“LayoutType”, StringValue(“RowFirst”));

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

mobility.Install(sensorNodes);

mobility.Install(sinkNode);

// Set up UDP applications for sensor nodes to send data to the sink node

uint16_t port = 4000;

OnOffHelper onOff(“ns3::UdpSocketFactory”, InetSocketAddress(sinkInterface.GetAddress(0, 1), port));

onOff.SetAttribute(“DataRate”, StringValue(“20Kbps”));

onOff.SetAttribute(“PacketSize”, UintegerValue(64));

ApplicationContainer apps;

for (uint32_t i = 0; i < sensorNodes.GetN(); i++) {

apps.Add(onOff.Install(sensorNodes.Get(i)));

}

apps.Start(Seconds(2.0));

apps.Stop(Seconds(10.0));

// Set up UDP sink on the sink node to receive data from sensors

PacketSinkHelper sinkHelper(“ns3::UdpSocketFactory”, InetSocketAddress(Ipv6Address::GetAny(), port));

ApplicationContainer sinkApp = sinkHelper.Install(sinkNode.Get(0));

sinkApp.Start(Seconds(1.0));

sinkApp.Stop(Seconds(10.0));

Simulator::Run();

Simulator::Destroy();

return 0;

}

  1. Configure Communication Parameters for WBAN

To enhance for low power and short-range interaction is necessary in WBANs. Configure the data rates, packet sizes, and intervals correctly:

  • Data Rate: Data rate is normally low like 20-100 Kbps.
  • Packet Size: Small packet sizes are general using energy.
  • Transmission Interval: Modify the OnOffApplication interval replicating the periodic sensor information.
  1. Implement Mobility Models (Optional)

Although WBANs are normally static related to the body then we can be utilized mobility models such as ConstantPositionMobilityModel or RandomWalk2dMobilityModel mimicking minor movement over the body.

Example:

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

mobility.Install(sensorNodes);

  1. Set Up Data Collection Applications

Replicate the data transmission from sensors to the sink node utilizing OnOffApplication, PacketSink, or custom applications. The sensor nodes can be transmitted packets periodically to signify health data, and the sink node gathers and executes this data.

Example with OnOffApplication:

OnOffHelper onOff(“ns3::UdpSocketFactory”, InetSocketAddress(sinkInterface.GetAddress(0, 1), port));

onOff.SetAttribute(“DataRate”, StringValue(“20Kbps”));

onOff.SetAttribute(“PacketSize”, UintegerValue(64));

  1. Evaluate WBAN Performance Metrics

We can examine the WBAN performance, to gather parameters like:

  • Throughput: From sensors to the sink, we estimate the data rate.
  • Latency: Monitor end-to-end delay for packets.
  • Packet Loss: For diverse WBAN sets up, confirm reliability.
  • Energy Consumption: Observe the interaction protocol’s energy efficiency if we contain energy model of NS3.

Accumulate performance data utilizing FlowMonitor:

FlowMonitorHelper flowmon;

Ptr<FlowMonitor> monitor = flowmon.InstallAll();

monitor->SerializeToXmlFile(“wban-flowmon.xml”, true, true);

  1. Visualize and Analyze Results
  • NetAnim: Envision the network that contains nodes and packet flows utilizing NetAnim.
  • Trace Files: We can examine the trace files for in-depth packet transmission and reception data.
  • Graphing Tools: Transfer data to graph the performance parameters such as latency, throughput, and packet delivery ratio.
  1. Experiment with Advanced WBAN Scenarios

When we contain a simple WBAN configuration then discover more advanced situations:

  • Adaptive Data Rate: Depends on the activity level or emergency scenarios, we replicate the dynamic modifications in data rate.
  • Energy Efficiency: Execute diverse transmission power levels and responsibility cycles minimizing energy consumption.
  • Interference Scenarios: In noisy environments, insert interference sources to experiment the WBAN reliability.
  • Health Applications: Replicate the certain health monitoring applications such as ECG or EEG by way of modifying the data rates and patterns.

Overall, we had revealed the basic fundamental techniques with instances that support you to easily understand the concepts and you can know how to initiate and examine the Wireless Body Area Network Projects using NS3. Additional required details will be updated later.

To initiate projects focused on Wireless Body Area Networks utilizing the NS3 tool, we offer assistance in identifying innovative and well-suited topics for you. Kindly provide all relevant project details to phdprojects.org, and we will support you in attaining optimal results. Our expertise encompasses low-power, short-range interactions, as well as low-power personal area networks, ensuring that we guide you towards achieving the best possible outcomes.