How to Implement Vehicle Traffic Analysis in NS2

To implement Vehicle Traffic Analysis in NS2, we usually mimic Vehicular Ad Hoc Networks (VANETs), in which vehicles interact with each other and with roadside units (RSUs). The main aim of vehicle traffic analysis can contains to learning vehicle-to-vehicle (V2V) communication, vehicle-to-infrastructure (V2I) communication, mobility patterns, traffic congestion, and data dissemination between vehicles. Here is a guide to implement the vehicle traffic analysis in ns2:

Steps to Implement Vehicle Traffic Analysis in NS2:

  1. Install NS2 and Mobility Extensions for VANET Simulation:
  • NS2: Make sure NS2 is installed and functioning appropriately. The basic installation of NS2 does not contain built-in support for vehicular networks, so we will need to incorporate additional mobility models or extensions.
  • Mobility Extensions: We can incorporate tools such as SUMO (Simulation of Urban Mobility) or use existing NS2 mobility models like Manhattan Grid Mobility or Random Waypoint Mobility to mimic vehicle movements. These models support to create realistic vehicle movement patterns.
  1. Integrate Mobility Models into NS2:
  • SUMO (Simulation of Urban Mobility) can be used to create realistic vehicle mobility traces that can be introduced into NS2.
  • Instead, NS2 has built-in mobility models such as Random Waypoint or Manhattan Grid; however these might not be as precise for vehicular scenarios.

For SUMO integration:

  • Install SUMO and create a mobility trace file.
  • Convert the SUMO trace into an NS2-compatible format using tools such as traceExporter.py (provided in SUMO tools).
  • Import the converted trace into NS2 using the mobilenode commands.
  1. Set Up the VANET Topology:
  • We need to generate a network of vehicles (nodes) and roadside units (RSUs). Each vehicle will be a node in NS2, and communication can be replicated using routing protocols such as AODV, DSDV, or even particular VANET protocols like GPSR, DVB-H, or DREAM.
  • Introduce the communication channels among nodes, and add RSUs for V2I communication.

Example OTcl script for vehicle network setup:

set ns [new Simulator]

set nf [open out.tr w]

$ns trace-all $nf

# Set up node configuration for VANET

set val(chan)           Channel/WirelessChannel

set val(prop)           Propagation/TwoRayGround

set val(netif)          Phy/WirelessPhy

set val(mac)            Mac/802_11

set val(ifq)            Queue/DropTail/PriQueue

set val(ll)             LL

set val(ant)            Antenna/OmniAntenna

set val(ifqlen)         50            ;# Max number of packets in ifq

set val(adhocRouting)   AODV          ;# Routing protocol used by vehicles

set val(x)              1000          ;# X dimension of the simulation area

set val(y)              1000          ;# Y dimension of the simulation area

set val(stop)           100.0         ;# Simulation stop time

# Create vehicle nodes

set numVehicles 10

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

set vehicle($i) [$ns node]

$vehicle($i) random-motion 0   ;# Disable random motion (we use mobility traces)

}

# Define mobility pattern (here, using a mobility file from SUMO)

$ns at 0.0 “source $vehicle(0) vehicle_mobility_trace.ns2”

$ns at 100.0 “finish”

proc finish {} {

global ns nf

$ns flush-trace

close $nf

exec nam out.nam &

exit 0

}

$ns run

  • In this sample, vehicles are configure as nodes, and mobility traces (generated using SUMO) are used for mimic realistic vehicle movement.
  1. Define the Communication Protocol for Vehicles:
  • Select an proper routing protocol such as AODV, DSDV, or a VANET-specific protocol like GPSR (Greedy Perimeter Stateless Routing).
  • Vehicles will interact using this routing protocol, and the network traffic (data packets) will be dispersed based on the protocol’s logic.

Example configuration of the AODV routing protocol:

set val(adhocRouting) AODV

  1. Simulate Communication Among Vehicles:
  • Configure the application layer to mimic data communication among vehicles, like Constant Bit Rate (CBR) traffic or File Transfer Protocol (FTP) traffic.
  • Vehicles will send and receive messages, and we can measure the network performance according to the gathered trace files.

Example: Setting up CBR traffic between two vehicles:

set udp [new Agent/UDP]

set null [new Agent/Null]

$ns attach-agent $vehicle(0) $udp

$ns attach-agent $vehicle(1) $null

$ns connect $udp $null

set cbr [new Application/Traffic/CBR]

$cbr attach-agent $udp

$cbr set packetSize_ 512

$cbr set rate_ 1Mb

$ns at 5.0 “$cbr start”

$ns at 95.0 “$cbr stop”

  • This script configures a basic UDP-based CBR traffic source on one vehicle, sending packets to another vehicle.
  1. Analyse Vehicle Traffic:
  • After executing the simulation, the generated trace file (out.tr) can be measured to measure network parameters such as:
    • Packet delivery ratio
    • Throughput
    • End-to-end delay
    • Vehicle mobility patterns
    • Congestion levels

Example AWK script to calculate packet delivery ratio:

awk ‘

BEGIN { sent_packets = 0; received_packets = 0; }

{

if ($1 == “+” && $4 == “UDP”) sent_packets++;

if ($1 == “r” && $4 == “UDP”) received_packets++;

}

END {

packet_delivery_ratio = (received_packets / sent_packets) * 100;

print “Packet Delivery Ratio:”, packet_delivery_ratio, “%”;

}’ out.tr

  • This script estimates the percentage of successfully delivered packets out of all sent packets.
  1. Use NAM for Visualizing Vehicle Movement and Communication:
  • NS2 creates a NAM (Network Animator) file (out.nam) that can utilize to envision the vehicle movement and communication. This helps in known on how the vehicles are moving and how information is being routed in the network.

To run NAM:

nam out.nam

  • In NAM, we can see vehicles moving in the network and packets being sent among nodes.
  1. Evaluate Key Metrics for Vehicle Traffic Analysis:
  • Throughput: Evaluate the data transfer rate among vehicles.
  • End-to-End Delay: Estimate the time it takes for a packet to travel from one vehicle to another.
  • Packet Loss: Count the number of packets lost during transmission because of mobility or congestion.
  • Traffic Congestion: Measure on how vehicle mobility affects the overall traffic in the network.

Example AWK script to calculate end-to-end delay:

awk ‘

BEGIN { total_delay = 0; packet_count = 0; }

{

if ($1 == “r” && $4 == “UDP”) {

delay = $2 – $11;  # Receive time – Send time

total_delay += delay;

packet_count++;

}

}

END {

avg_delay = total_delay / packet_count;

print “Average End-to-End Delay:”, avg_delay, “seconds”;

}’ out.tr

  1. Optimize the Simulation (Optional):
  • Once the simulation is done, we can tweak the mobility models, traffic patterns, or protocol metrics to enhance the vehicular communication. For example, we could adapt the transmission range of vehicles or test with diverse routing protocols to enhance network performance.

In the above information were clearly showed how the Vehicle Traffic Analysis will perform using the ns2 simulation tool. We also deliver more information regarding the Vehicle Traffic Analysis.

For the implementation of vehicle traffic analysis using the NS2 tool, we invite you to reach out to us. We offer customized services and exceptional research support to meet your needs. Get best developers guidance on vehicle-to-vehicle (V2V) communication, vehicle-to-infrastructure (V2I) communication, mobility patterns, traffic congestion, and data dissemination between vehicles related to your concepts.