How to Implement 4D MANET Massive in NS2

To implement the 4D Mobile Ad Hoc Network (MANET) Massive in NS2, we have to simulate mobile nodes within a four-dimensional space. Usually old-fashioned MANET simulations performs in 2D or 3D space however, in this case the 4D can indicate another variable like time-related alterations in network parameters or mobility through various phases of the network (for instance: temporal variations in mobility or node properties like energy, bandwidth, or connectivity).

To simulate a 4D MANET in NS2, we’ll need to:

Prototype nodes’ mobility in 3D space.
Simulate varies over time to denote the fourth dimension like variations in node properties, connectivity, and network performance.
Replicate a massive network with a massive amount of nodes (hundreds or thousands).

Here in the following below, you can use the given guide to achieve this in ns2:

Step-by-Step Implementation:

NS2 Setup

Start by configuring a simplified NS2 simulation scenario as well as defining the large number of mobile nodes with 3D mobility.

# Create an NS2 simulator instance

set ns [new Simulator]

# Open trace files for logging the simulation

set tracefile [open “4d_manet_massive.tr” w]

set namfile [open “4d_manet_massive.nam” w]

$ns trace-all $tracefile

$ns namtrace-all-wireless $namfile 1000 1000 ;# 2D visualization grid for simplicity

# Define a 3D topography (spatial dimensions)

set topo [new Topography]

$topo load_flatgrid 1000 1000

# Define the channel and physical layer components

set chan_1_ [new Channel/WirelessChannel]

set prop [new Propagation/TwoRayGround]

set netif [new Phy/WirelessPhy]

set mac [new Mac/802_11]

set ll [new LL]

set ifq [new Queue/DropTail/PriQueue]

set ant [new Antenna/OmniAntenna]

# Configure the wireless nodes

$ns node-config -adhocRouting AODV \

-llType $ll \

-macType $mac \

-ifqType $ifq \

-ifqLen 50 \

-antType $ant \

-propType $prop \

-phyType $netif \

-channel $chan_1_ \

-topoInstance $topo

Modeling 3D Mobility for Nodes

For the 3D movement (x, y, z), we have to attach motion allied with z-axis by extending the node mobility models which will grant us to replicate the nodes traveling across a 3D environment.

# Procedure to set 3D position for nodes

proc set_3d_position {node x y z} {

$node set X_ $x

$node set Y_ $y

$node set Z_ $z ;# Set z-axis (altitude) for 3D positioning

}

# Define a procedure for random 3D mobility

proc random_3d_mobility {node max_x max_y max_z speed} {

global ns

set x [expr rand() * $max_x]

set y [expr rand() * $max_y]

set z [expr rand() * $max_z]

set dest_x [expr rand() * $max_x]

set dest_y [expr rand() * $max_y]

set dest_z [expr rand() * $max_z]

set time [expr ($x – $dest_x) / $speed]

# Set initial position and move the node in 3D

$node setdest $dest_x $dest_y $time

$node set Z_ $dest_z ;# Move along z-axis as well

}

# Example: Assigning random 3D mobility for node 1

random_3d_mobility $node(1) 1000 1000 500 10 ;# 1000x1000x500 3D space, 10 m/s speed

Introducing the Fourth Dimension (Time-Dependent Network Changes)

In the context of 4D MANET, the fourth dimension could indicate temporal differences in network properties, mobility patterns, or node states over time. This could have:

Energy consumption: Nodes may utilize energy over time, minimizing their potential to interact.
Bandwidth or connectivity changes: When the time progresses, nodes might experience changing connectivity or bandwidth.
Mobility patterns: Nodes may follow various movement phases over time.

We can model these time-reliable variations using events that activate state alterations in the nodes or the network.

Example: Varying Node Properties Over Time

# Procedure to simulate energy consumption over time

proc update_node_energy {node initial_energy decay_rate} {

global ns

set current_energy $initial_energy

set interval 10.0 ;# Update energy every 10 seconds

# Decay energy over time

for {set t 0.0} {$t < 100.0} {incr t $interval} {

set current_energy [expr $current_energy – $decay_rate * $interval]

if {$current_energy <= 0} {

puts “Node $node has depleted its energy at time $t”

break

}

$ns at $t “puts Node $node has energy $current_energy”

}

# Example: Start with 100% energy and decay at a rate of 1% per second

update_node_energy $node(1) 1.0 0.01

Creating Massive Number of Nodes

Replicate a massive network with hundreds or thousands of nodes by developing the nodes using a loop and allocate each node a random 3D location and mobility pattern.

# Create a large number of nodes (e.g., 1000 nodes)

set num_nodes 1000

for {set i 0} {$i < $num_nodes} {incr i} {

set node($i) [$ns node]

$node($i) random-motion 0 ;# Disable random motion by default

# Assign random 3D positions to the node

set_3d_position $node($i) [expr rand() * 1000] [expr rand() * 1000] [expr rand() * 500]

# Set random mobility for the node in 3D space

random_3d_mobility $node($i) 1000 1000 500 10

}

Traffic Setup and QoS

Imitate communication in this 4D MANET by setting up traffic amongst nodes. Use UDP or TCP agents for various kinds of traffic, and mimic how the network varies over time impacts performance.

# Create a UDP traffic flow from node 1 to node 500

set udp_src [new Agent/UDP]

set udp_sink [new Agent/Null]

set cbr [new Application/Traffic/CBR]

# Attach agents to nodes

$ns attach-agent $node(1) $udp_src

$ns attach-agent $node(500) $udp_sink

# Connect UDP source to sink

$ns connect $udp_src $udp_sink

# Configure CBR traffic for continuous transmission

$cbr attach-agent $udp_src

$cbr set packetSize_ 512

$cbr set rate_ 100Kb ;# Communication data rate

# Start the traffic at time 1.0 seconds and stop at time 100.0

$ns at 1.0 “$cbr start”

$ns at 100.0 “$cbr stop”

Dynamic Network Topology Changes

Denote 4D changes by occasionally alter node properties or amend routing activities dynamically during the simulation. This could indicate network adaptation because of mobility or changing connectivity over time.

# Periodically change mobility pattern or bandwidth for a node (e.g., every 20 seconds)

proc change_node_mobility {node interval max_x max_y max_z speed} {

global ns

for {set t 0.0} {$t < 100.0} {incr t $interval} {

random_3d_mobility $node $max_x $max_y $max_z $speed

$ns at $t “puts Changing mobility for node $node at time $t”

}

# Apply dynamic mobility changes for node 1 every 20 seconds

change_node_mobility $node(1) 20.0 1000 1000 500 5

Routing Configuration (AODV for Dynamic MANET)

For large-scale 4D MANETs, AODV (Ad hoc On-Demand Distance Vector) routing is appropriate because of its dynamic route findings. Routes are accomplished on demand, and the protocol adapts to differences in the network topology.

# AODV routing protocol for MANET nodes

$ns node-config -adhocRouting AODV

Running the Simulation

Execute the simulation for a large number of nodes, dynamic mobility, and time-based variations in node properties.

# Set simulation end time

$ns at 200.0 “finish”

proc finish {} {

global ns tracefile namfile

$ns flush-trace

close $tracefile

close $namfile

exit 0

}

# Run the simulation

$ns run

Analysis and Results

Once the simulation is finished, evaluate the trace files to monitor how time-dependent changes (the fourth dimension) impact the MANET’s performance:

Throughput: Compute how the variations in node properties influence communication.
Delay: Assess delays initiated by node movement or varying connectivity.
Packet Loss: Verify how mobility and network differs over time lead to packet loss.

This manual offers the detailed guide on how to implement 4D (Mobile Ad Hoc Networks) MANET Massive Users in ns2 environment by modeling the 3D Mobility for Nodes and then launch the fourth dimensional space to establish the massive amount of users for the evaluation.

Your greatest supporter for assistance in guiding you through the 4D MANET Massive implementation in ns2tool will be ns2project.com. For the best results, provide us the details of your project while we work on network performance