To implement network power adjustment in ns3, we need to dynamically adjusting the transmission power of nodes. For applying this we need to follow several steps, such as reducing interference, saving energy, or improving connectivity. This type of adjustment mainly use in wireless networks based on their environment or network conditions, nodes need to adapt their power levels.
Below given steps helps in implementing network adjustment of power in ns3.
Step-by-step guide to implement network power adjustment 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 Network Power Adjustment Simulation Script
We will create a script that sets up a network with nodes that can adjust their transmission power dynamically based on certain conditions.
#include “ns3/core-module.h”
#include “ns3/network-module.h”
#include “ns3/internet-module.h”
#include “ns3/point-to-point-module.h”
#include “ns3/mobility-module.h”
#include “ns3/applications-module.h”
#include “ns3/wifi-module.h”
#include “ns3/flow-monitor-module.h”
using namespace ns3;
NS_LOG_COMPONENT_DEFINE(“NetworkPowerAdjustmentExample”);
// Function to adjust the transmission power of nodes
void AdjustTransmissionPower(Ptr<WifiNetDevice> wifiNetDevice, double newPower)
{
Ptr<WifiPhy> wifiPhy = wifiNetDevice->GetPhy();
wifiPhy->SetTxPowerStart(newPower);
wifiPhy->SetTxPowerEnd(newPower);
NS_LOG_UNCOND(“Adjusted transmission power to ” << newPower << ” dBm”);
}
int main(int argc, char *argv[])
{
CommandLine cmd;
cmd.Parse(argc, argv);
// Create nodes
NodeContainer nodes;
nodes.Create(10); // Ten nodes in total
// Set up mobility model
MobilityHelper mobility;
mobility.SetPositionAllocator(“ns3::GridPositionAllocator”,
“MinX”, DoubleValue(0.0),
“MinY”, DoubleValue(0.0),
“DeltaX”, DoubleValue(10.0),
“DeltaY”, DoubleValue(10.0),
“GridWidth”, UintegerValue(5),
“LayoutType”, StringValue(“RowFirst”));
mobility.SetMobilityModel(“ns3::ConstantPositionMobilityModel”);
mobility.Install(nodes);
// Set up WiFi
WifiHelper wifi;
wifi.SetRemoteStationManager(“ns3::AarfWifiManager”);
WifiMacHelper mac;
Ssid ssid = Ssid(“ns-3-ssid”);
mac.SetType(“ns3::StaWifiMac”,
“Ssid”, SsidValue(ssid),
“ActiveProbing”, BooleanValue(false));
YansWifiPhyHelper phy = YansWifiPhyHelper::Default();
YansWifiChannelHelper channel = YansWifiChannelHelper::Default();
phy.SetChannel(channel.Create());
NetDeviceContainer devices = wifi.Install(phy, mac, nodes);
mac.SetType(“ns3::ApWifiMac”,
“Ssid”, SsidValue(ssid));
NetDeviceContainer apDevices = wifi.Install(phy, mac, nodes.Get(0));
// 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);
address.Assign(apDevices);
// Install applications to generate traffic
uint16_t port = 9;
OnOffHelperonoff(“ns3::UdpSocketFactory”, Address(InetSocketAddress(interfaces.GetAddress(1), port)));
onoff.SetConstantRate(DataRate(“1Mbps”));
ApplicationContainer apps = onoff.Install(nodes.Get(0));
apps.Start(Seconds(1.0));
apps.Stop(Seconds(10.0));
PacketSinkHelpersink(“ns3::UdpSocketFactory”, Address(InetSocketAddress(Ipv4Address::GetAny(), port)));
apps = sink.Install(nodes.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();
// Adjust the transmission power of a node at a specific time
Simulator::Schedule(Seconds(5.0),&AdjustTransmissionPower, DynamicCast<WifiNetDevice>(devices.Get(0)), 10.0);
// Run the simulation
Simulator::Stop(Seconds(15.0));
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/network-power-adjustment-example
Step 4: Analyze Results
The simulation script sets up a network topology with nodes and dynamically adjusts the transmission power of a node at a specific time. The positions, velocities, and power adjustments of the nodes are logged. 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 network power adjustment simulation, consider the following:
1. Dynamic Power Adjustment Algorithms
Implement dynamic power adjustment algorithms that adapt the transmission power of nodes based on network conditions, interference levels, or application requirements.
2. Advanced Mobility Models
Incorporate advanced mobility models to simulate more realistic movement patterns, such as vehicles in a VANET scenario or drones in a UAV network.
3. Communication Protocols
Integrate communication protocols that optimize data routing and resource allocation based on the adjusted power levels.
4. Performance Metrics
Collect and analyze additional metrics such as energy consumption, network latency, and packet delivery ratio to evaluate the performance of the power adjustment algorithms.
5. Real-World Scenarios
Simulate real-world scenarios such as smart cities, industrial IoT deployments, or disaster recovery networks to test the effectiveness of the power adjustment approach in practical applications.
From the given above steps and example we can completely understand the network adjustment of power in ns3, by dynamically adjusting the transmission power of nodes while simulating the network using packetsinkhelper we can analyze the result.
For expert assistance with implementing Network Adjustment of power in the ns3tool, feel free to reach out to us. We can provide guidance and support to help you with your implementation. Share your project details with us to receive performance results and further guidance.