How to Implement Network Obstacle Prediction in NS2

To implement Network Obstacle Prediction in NS2, we will need to mimic on how difficulty in the environment impacts the network communication and then predict the effects of these obstacles on node mobility, signal strength, and overall network performance. Since NS2 doesn’t natively replicate physical obstacles, we can abstract the effects of obstacles by modelling their impacts on packet delivery, signal degradation, and routing behaviour.

Here’s how to implement Network Obstacle Prediction in NS2:

Step-by-Step Implementation:

Understanding Obstacle Prediction

Obstacle prediction refers to modelling how physical obstructions like buildings, trees, or mountains impacts signal propagation, packet loss, and node mobility.
In NS2, we can denote the obstacles by adapting the packet reception, signal strength, and mobility models to mimic the presence of obstacles in the network environment.
We can predict the effects of these obstacles by monitoring signal strength, packet loss rates, and how the nodes adapt their routing or transmission strategies.

Approach for Simulating Obstacles in NS2

Signal Strength Degradation: To mimic obstacles by minimizing the signal strength or establishing packet errors when nodes are within the range of an obstacle.
Mobility Prediction: Forecast the effects of obstacles on node mobility by adapting the node’s movement when it encounters an obstacle.
Routing Behavior: Adapt routing protocols according to obstacles, in which nodes need to take alternate routes when they encounter an obstruction.

Basic Steps for Obstacle Prediction Simulation in NS2

Define Obstacles: Configure virtual obstacles within the simulation environment, that denoted by certain areas in which signal strength is minimized or in which the mobility is limited.
Monitor Signal Strength and Packet Loss: Track signal strength degradation and packet loss when nodes move into areas impacted by obstacles.
Predict and Adjust Mobility: Adapt node mobility to account for obstacles, either by preventing them or adapting the route when obstacles are detected.

Modifying the Simulation to Introduce Obstacles

To execute obstacle prediction in NS2, we need to adjust the physical layer to mimic how obstacles impacts packet transmission and reception.

Step-by-Step Implementation

Step 1: Define Obstacles in the Simulation Environment

In the simulation, describe the coordinates and size of obstacles. These can be regions in the simulation area in which signal degradation occurs or where nodes cannot move.

# Define obstacles as rectangular areas in the simulation area

# Format: {xmin ymin xmax ymax}

set obstacle_1 {300 300 400 400} ;# Example obstacle

set obstacle_2 {600 600 700 700} ;# Another obstacle

Step 2: Adjust Packet Reception Based on Obstacles

Adjust the physical layer to mimic signal degradation when nodes are within the range of an obstacle. Open ~/ns-2.35/tcl/lib/wireless-phy.tcl and adjust the packet reception logic.

# Function to check if a node is within an obstacle

proc is_within_obstacle {x y obstacle} {

set xmin [lindex $obstacle 0]

set ymin [lindex $obstacle 1]

set xmax [lindex $obstacle 2]

set ymax [lindex $obstacle 3]

if {($x >= $xmin) && ($x <= $xmax) && ($y >= $ymin) && ($y <= $ymax)} {

return 1 ;# Node is within the obstacle

} else {

return 0 ;# Node is not within the obstacle

}

# Modify packet reception to include obstacle prediction

proc Phy/WirelessPhy::recv {packet} {

set node [$self node]

set x [$node set X_]

set y [$node set Y_]

# Check if the node is within any obstacle

if {[is_within_obstacle $x $y $::obstacle_1] || [is_within_obstacle $x $y $::obstacle_2]} {

# Simulate signal degradation (increase packet error rate or drop the packet)

set random_val [expr rand()]

if {$random_val < 0.5} {

# Drop the packet due to the obstacle interference

drop $packet

return

}

# If no obstacle interference, forward the packet to the upper layer

$self-up-target $packet

}

Step 3: Predict and Adjust Mobility When Obstacles Are Detected

Adjust the mobility model to adapt node movement when an obstacle is classified. In the simulation, nodes will prevent obstacles by adapting their destination coordinates.

# Function to adjust node destination if it moves towards an obstacle

proc adjust_mobility_for_obstacle {node obstacle} {

set x [$node set X_]

set y [$node set Y_]

set dest_x [$node setdest x]

set dest_y [$node setdest y]

if {[is_within_obstacle $dest_x $dest_y $obstacle]} {

# Adjust the destination to avoid the obstacle

set new_dest_x [expr $dest_x + 50] ;# Example adjustment

set new_dest_y [expr $dest_y + 50]

$node setdest $new_dest_x $new_dest_y 10.0 ;# Adjust speed to 10.0 m/s

}

# Apply obstacle avoidance during mobility

for {set i 0} {$i < $opt(nn)} {incr i} {

adjust_mobility_for_obstacle $node_($i) $::obstacle_1

adjust_mobility_for_obstacle $node_($i) $::obstacle_2

}

Step 4: Update the TCL Simulation Script to Simulate Obstacles

We will need a TCL script that mimics a network scenario with obstacles and node mobility. Nodes will prevent difficulties during movement and experience signal degradation when within obstacle regions.

# Create a simulator instance

set ns [new Simulator]

# Create trace and nam files for output

set tracefile [open obstacle_prediction.tr w]

set namfile [open obstacle_prediction.nam w]

$ns trace-all $tracefile

$ns namtrace-all $namfile

# Define network topology

set topo [new Topography]

$topo load_flatgrid 1000 1000 ;# Simulation area: 1000×1000 meters

# Create the General Operations Director (GOD)

set god_ [create-god 10] ;# 10 nodes

# Define obstacles (as rectangular areas)

set obstacle_1 {300 300 400 400}

set obstacle_2 {600 600 700 700}

# Set node parameters

set opt(chan) Channel/WirelessChannel

set opt(prop) Propagation/TwoRayGround

set opt(netif) Phy/WirelessPhy

set opt(mac) Mac/802_11

set opt(ifq) Queue/DropTail/PriQueue

set opt(ll) LL

set opt(ant) Antenna/OmniAntenna

set opt(x) 1000

set opt(y) 1000

# Set number of nodes

set opt(nn) 10 ;# Number of nodes

# Create nodes and define initial positions

for {set i 0} {$i < $opt(nn)} {incr i} {

set node_($i) [$ns node]

$node_($i) random-motion 1 ;# Enable random motion for nodes

}

# Mobility model: Avoid obstacles

proc start_mobility {} {

global ns node_ opt

for {set i 0} {$i < $opt(nn)} {incr i} {

adjust_mobility_for_obstacle $node_($i) $::obstacle_1

adjust_mobility_for_obstacle $node_($i) $::obstacle_2

}

# Start mobility at 1.0 second

$ns at 1.0 “start_mobility”

# Traffic generation

proc start_traffic {} {

global ns node_ opt

# Create UDP agents and attach them to nodes

for {set i 0} {$i < $opt(nn)} {incr i} {

set udp_($i) [new Agent/UDP]

set null_($i) [new Agent/Null]

$ns attach-agent $node_($i) $udp_($i)

$ns attach-agent $node_($i) $null_($i)

# Generate CBR traffic

set cbr_($i) [new Application/Traffic/CBR]

$cbr_($i) set packetSize_ 512

$cbr_($i) set interval_ 0.1

$cbr_($i) attach-agent $udp_($i)

# Connect UDP agents for communication between nodes

$ns connect $udp_($i) $null_($i)

}

# Start the traffic at 1.0 second

$ns at 1.0 “start_traffic”

# Run the simulation

$ns at 100.0 “finish”

# End simulation procedure

proc finish {} {

global ns tracefile namfile

close $tracefile

close $namfile

$ns halt

}

# Run the simulation

$ns run

Explanation of the Script

Obstacle Definition: Obstacles are defined as rectangular areas, like obstacle_1 {300 300 400 400} and obstacle_2 {600 600 700 700}, that denotes regions in the network in which signal degradation or mobility restrictions occur.
Packet Reception Impact: The recv function mimics the impact of obstacles on packet reception by establishing packet loss according to a random probability when nodes are within obstacle regions.
Mobility Adjustment: The mobility modifies the function adjust_mobility_for_obstacle avoids nodes from moving into difficulty areas by modifying their destination when they identify an obstacle.

Running the Simulation

Save the modified wireless-phy.tcl file and the TCL script (obstacle_prediction.tcl).
execute the simulation using:

ns obstacle_prediction.tcl

Analysing Results

After executing the simulation, measure the trace file (obstacle_prediction.tr) to monitor on how obstacles impacts packet transmission and node mobility.
You can look for:
- Packet Delivery Ratio: How many packets successfully reach their destination, particularly in the presence of obstacles?
- Mobility Patterns: How nodes adapt their movement to prevent obstacles.

Further Enhancements

Dynamic Obstacles: Replicate obstacles that move or change over time, that needs a nodes to enthusiastically adapt their routing and mobility.
Advanced Routing Adjustments: Incorporate obstacle prediction into routing protocols because of that nodes proactively route around obstacle ranges.
Signal Strength Prediction: utilize more advanced signal strength models such as path loss models to better simulate how obstacles affects the communication.

We clearly provide the detailed implementation process for network obstacle prediction that were implemented by using ns2 tool that has deliberated to learn the core components of obstacle prediction then we need to mimic the network scenario to evaluate the outcomes. More information regarding the network obstacle prediction will be shared in the further setup.

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