**How to Implement 4D Wireless Sensor Modeling in NS2**

To implement the 4D wireless sensor modeling within NS2 (Network Simulator 2) is more difficult than 3D modeling since the fourth dimension is frequently deliberated time or another metrics like environmental conditions, mobility patterns, or node states. In the context of the 4D model wireless sensor networks (WSNs), can denote the sensor node movement within 3D space including an added dynamic metrics such as time-varying environmental conditions, energy levels, or communication dynamics which evolve across time. The following is simple procedure on how to execute 4D wireless sensor modeling in NS2, including the assumption which the fourth dimension is time or another dynamic network characteristic.

**Step-by-Step Implementation:**

**Key Aspects of 4D Modeling in WSN:**

**3D Movement**: These nodes are move in a 3D space (x, y, z coordinates).**Dynamic Time or State (Fourth Dimension)**: The state of nodes such as energy, traffic, or environment which alters over time, creating it the fourth dimension.

**Understand 4D Wireless Sensor Modeling**

In 4D modeling:

- The 3D space is signified by the x, y, and z coordinates.
- The fourth dimension can be time, however we can expand it to denote any time-varying parameter like:
**Energy depletion**: A node’s energy reduces over time.**Environmental conditions**: Signal propagation or interference modifies dynamically.**Mobility patterns**: These nodes may move in 3D space, and their performance changes as time progresses.

**Extend 3D Node Positioning for 4D Support**

In the simulation NS2, we can already expand the node positioning to 3D space (x, y, z). To create it 4D, we want to actively update a particular parameter such as energy, signal propagation, or mobility patterns over time.

**Modify the ****MobileNode** **Class for 4D:**

We can extend the MobileNode class to accumulate and up to date 3D coordinates in addition to the fourth parameter, like an energy or signal propagation.

**Example C++ Code for 4D Wireless Sensor Node:**

class MobileNode : public Node {

public:

MobileNode();

// Get and set position in 3D (x, y, z) with time-varying properties

void get_position(double &x, double &y, double &z);

void set_position(double x, double y, double z);

// Handle the fourth dimension: time-varying energy or signal strength

void updateFourthDimension(double time);

protected:

double z_; // z-coordinate for 3D

double energy_; // Time-varying energy, as an example of the fourth dimension

};

// Constructor to initialize 4D properties

MobileNode::MobileNode() : Node(), z_(0.0), energy_(100.0) {

}

// Get the current position in 3D space

void MobileNode::get_position(double &x, double &y, double &z) {

x = X_;

y = Y_;

z = z_;

}

// Set position in 3D space

void MobileNode::set_position(double x, double y, double z) {

X_ = x;

Y_ = y;

z_ = z;

}

// Update the fourth dimension (e.g., energy decreases over time)

void MobileNode::updateFourthDimension(double time) {

energy_ -= time * 0.5; // Decrease energy over time (as an example)

if (energy_ < 0) energy_ = 0;

}

The above code describes a MobileNode class, which manages the 3D positioning (x, y, z) and a fourth dimension (in this case, energy) that modifies over time.

**Time as the Fourth Dimension**

If time is the fourth dimension then it is implicit in the simulation, as entire events are time-scheduled in the simulation NS2. We can be used time-based events to up-to-date the state of the nodes or network metrics over time.

For instance, we can periodically update their energy levels of nodes, and alter their communication performance, or activate events such as link failures because of the time-based changes.

**Example Tcl Script for Time-Based Updates:**

# Create a simulator instance

set ns [new Simulator]

# Create sensor nodes

set node1 [$ns node]

set node2 [$ns node]

# Set initial positions in 3D space (x, y, z)

$node1 set X_ 50.0

$node1 set Y_ 60.0

$node1 set Z_ 70.0

$node2 set X_ 100.0

$node2 set Y_ 110.0

$node2 set Z_ 120.0

# Define a function to update the time-varying parameter (e.g., energy)

proc update_energy {} {

global ns node1 node2

set time [$ns now]

# Call updateFourthDimension in C++ (energy depletion over time)

$node1 updateFourthDimension $time

$node2 updateFourthDimension $time

# Schedule the next update in 1 second

$ns at [expr $time + 1.0] “update_energy”

}

# Start the energy update process

$ns at 1.0 “update_energy”

# Define mobility for 3D space (if necessary)

$node1 setdest 200.0 250.0 50.0 5.0 ;# Move to a new 3D location

# Define communication, routing, etc.

$ns rtproto AODV

# Run the simulation

$ns run

In this Tcl script:

- Energy depletion is modeled as the fourth dimension and it updated each second.
- The energy of ever node reduces over the time, mimicking a dynamic, time-varying network.

**Mobility Patterns as the Fourth Dimension**

In a 4D model, the fourth dimension can signify mobility alters over the time. These nodes can move via 3D space, however their movement patterns modify over time. For instance, they might change speed, direction, or mode of operation according to some external factors.

**Example:**

- At time t = 0, the node moves in one direction.
- After t = 100 seconds, the node changes its mobility pattern (speed, direction).

**Environmental Conditions as the Fourth Dimension**

The fourth dimension can also signify the environmental changes which impact the signal propagation, interference, or the node’s communication performance. For instance, a sensor node’s ability to communicate would rely on climate conditions or terrain modifies over the time.

**Energy Levels as the Fourth Dimension**

A general fourth dimension within wireless sensor networks is energy levels. We can model the energy depletion over time that impacting how long nodes can communicate or involve in the network.

In the MobileNode class, we executed the energy as a time-varying property. We can expand it to replicate various energy consumption rates for communication, sensing, or other tasks.

**Simulate a 4D Wireless Sensor Network in NS2**

When the 4D elements (3D space and time-varying parameters) are executed, we can replicate the network in NS2.

**Example Tcl Script for 4D Simulation:**

# Create a simulator instance

set ns [new Simulator]

# Create sensor nodes

set node1 [$ns node]

set node2 [$ns node]

# Set initial positions in 3D space (x, y, z)

$node1 set X_ 50.0

$node1 set Y_ 60.0

$node1 set Z_ 70.0

$node2 set X_ 100.0

$node2 set Y_ 110.0

$node2 set Z_ 120.0

# Define a function to update the time-varying parameter (energy)

proc update_time_varying_parameters {} {

global ns node1 node2

set time [$ns now]

# Decrease energy over time (example of the fourth dimension)

$node1 updateFourthDimension $time

$node2 updateFourthDimension $time

# Schedule the next update in 1 second

$ns at [expr $time + 1.0] “update_time_varying_parameters”

}

# Start the process of updating time-varying parameters

$ns at 1.0 “update_time_varying_parameters”

# Set up mobility for 3D movement (if necessary)

$node1 setdest 200.0 250.0 50.0 5.0 ;# Move to a new location in 3D

# Set up traffic sources and routing

set udp1 [new Agent/UDP]

set udp2 [new Agent/UDP]

set null [new Agent/Null]

$ns attach-agent $node1 $udp1

$ns attach-agent $node2 $udp2

$ns attach-agent $node1 $null

$ns connect $udp1 $null

$ns connect $udp2 $null

# Define a CBR traffic generator

set cbr [new Application/Traffic/CBR]

$cbr set packetSize_ 512

$cbr set interval_ 0.1

$cbr attach-agent $udp1

# Start traffic

$ns at 1.0 “$cbr start”

# Run the simulation

$ns run

**Analysis and Metrics**

After simulating the 4D WSN, we can examine:

**Packet delivery ratio**: Evaluate the success rate of the data packets.**Energy consumption**: Follow the balance energy of every node over time.**End-to-end delay**: Assess how the time-varying conditions (the fourth dimension) impact the communication.

- The following is basic process on how to implement the 4D wireless sensor modeling in NS2, containing the assumption that the fourth dimension is time or another dynamic network characteristic.

As demonstrated, with the support of executing methods regarding the 4D Wireless Sensor Modeling that were executed and analysed in the simulation platform NS2. We will offer more details about this topic depending on your requirements.

To implement 4D Wireless Sensor Modeling using the NS2 tool, please feel free to contact us. We are prepared to assist you with a concise explanation and timely delivery. Our team specializes in environmental conditions, energy levels, and communication dynamics, ensuring optimal results. Therefore, you can expect customized support tailored to your specific requirements.