To simulate Swarm Networking projects using NS2 has includes generating a network in which the multiple autonomous agents like robots or drones interact and act as a team to perform tasks. Swarm networks are usually utilized in scenarios such as search and rescue, environmental monitoring, and surveillance. These networks are decentralized, self-organizing, and depend on communication among nodes for coordination. The team at phdprime.com is prepared to assist you with customized simulation outcomes; contact us for innovative assistance.
Here’s a step-by-step guide to simulate Swarm Networking in NS2:
Steps to Simulate Swarm Networking Projects in NS2
- Install NS2
Make sure that NS2 is installed on the system. If not, install it:
sudo apt-get install ns2
- Key Components in Swarm Networking
- Swarm Agents (Nodes): Individual nodes that signify autonomous agents, like drones or robots.
- Communication Model: Nodes interact with each other using wireless links (Wi-Fi, ad-hoc protocols, etc.).
- Coordination Algorithm: Swarm members communicate to coordinate movements or distribute information.
- Mobility Model: The nodes are usual mobile and their movement’s required to be defined (random or coordinated).
- Design the Swarm Network Topology
Each node in the swarm performs as a mobile node that communicates with other swarm members. The communication can be either peer-to-peer or with a central node that coordinates the swarm.
Example Topology:
- Swarm Nodes (Mobile Nodes): Representing drones or robots in the swarm.
- Optional Control Node (Fixed Node): For scenarios in which a centralized controls system communicate with the swarm.
- TCL Script for Swarm Networking Simulation
4.1 Define Nodes
In a swarm network, each agent (robot or drone) is a node. We will describe numerous nodes that communicate with each other.
# Create the simulator object
set ns [new Simulator]
# Open trace and NAM files
set tracefile [open “swarm_network.tr” w]
$ns trace-all $tracefile
set namfile [open “swarm_network.nam” w]
$ns namtrace-all $namfile
# Define simulation parameters
set val(chan) Channel/WirelessChannel ;# Wireless channel for communication
set val(prop) Propagation/TwoRayGround ;# Propagation model
set val(mac) Mac/802_11 ;# MAC protocol for wireless communication
set val(ifq) Queue/DropTail/PriQueue ;# Interface queue
set val(ll) LL ;# Link layer
set val(ant) Antenna/OmniAntenna ;# Antenna model
set val(ifqlen) 50 ;# Interface queue length
set val(rp) AODV ;# Routing protocol (for swarm communication)
# Node configuration
$ns node-config -adhocRouting $val(rp) \
-llType $val(ll) \
-macType $val(mac) \
-ifqType $val(ifq) \
-ifqLen $val(ifqlen) \
-antType $val(ant) \
-propType $val(prop) \
-channelType $val(chan)
# Create nodes for swarm agents (drones/robots)
set swarm1 [$ns node]
set swarm2 [$ns node]
set swarm3 [$ns node]
set swarm4 [$ns node]
set swarm5 [$ns node]
set control_node [$ns node] ;# Optional control center node
# Set initial positions for swarm agents
$swarm1 set X_ 50
$swarm1 set Y_ 100
$swarm1 set Z_ 0.0
$swarm2 set X_ 100
$swarm2 set Y_ 150
$swarm2 set Z_ 0.0
$swarm3 set X_ 150
$swarm3 set Y_ 200
$swarm3 set Z_ 0.0
$swarm4 set X_ 200
$swarm4 set Y_ 250
$swarm4 set Z_ 0.0
$swarm5 set X_ 250
$swarm5 set Y_ 300
$swarm5 set Z_ 0.0
$control_node set X_ 200
$control_node set Y_ 350
$control_node set Z_ 0.0
- Define Communication between Nodes
Swarm members interact directly with each other. Utilize wireless links to replicate peer-to-peer communication.
5.1 Communication between Swarm Nodes
# Define communication between swarm agents (peer-to-peer)
$ns duplex-link $swarm1 $swarm2 10Mb 20ms DropTail
$ns duplex-link $swarm2 $swarm3 10Mb 20ms DropTail
$ns duplex-link $swarm3 $swarm4 10Mb 20ms DropTail
$ns duplex-link $swarm4 $swarm5 10Mb 20ms DropTail
5.2 Communication between Swarm and Control Node (Optional)
In some scenarios, the swarm interact with a central node.
# define communication between swarm agents and control node
$ns duplex-link $swarm1 $control_node 10Mb 15ms DropTail
- Configure Traffic Patterns
Swarm nodes usually transmit status updates, sensor data, or coordination messages to each other. We need to describe this traffic using TCP for reliable communication or UDP for faster, less reliable communication.
6.1 TCP Traffic for Reliable Communication
# TCP agent for communication between swarm1 and control node
set tcp_swarm1 [new Agent/TCP]
$ns attach-agent $swarm1 $tcp_swarm1
# TCP sink at the control node
set tcp_control [new Agent/TCPSink]
$ns attach-agent $control_node $tcp_control
# Connect TCP agent to sink
$ns connect $tcp_swarm1 $tcp_control
# Define application traffic (e.g., status updates from swarm1 to control node)
set app_swarm1 [new Application/Traffic/CBR]
$app_swarm1 attach-agent $tcp_swarm1
$app_swarm1 set packetSize_ 512
$app_swarm1 set interval_ 0.05
$ns at 1.0 “$app_swarm1 start”
6.2 UDP Traffic for Sensor Data
# UDP agent for sensor data from swarm2
set udp_swarm2 [new Agent/UDP]
$ns attach-agent $swarm2 $udp_swarm2
# UDP sink at the control node
set sink_udp_control [new Agent/Null]
$ns attach-agent $control_node $sink_udp_control
# Connect UDP agent to sink
$ns connect $udp_swarm2 $sink_udp_control
# Define application traffic for sensor data from swarm2
set app_swarm2 [new Application/Traffic/CBR]
$app_swarm2 attach-agent $udp_swarm2
$app_swarm2 set packetSize_ 512
$app_swarm2 set interval_ 0.1
$ns at 2.0 “$app_swarm2 start”
- Define Mobility for Swarm Nodes
Swarm nodes are mobile, and their movement is usually based on tasks or algorithms. We can utilize random waypoint mobility models or specific paths for coordinated movement.
# Define mobility for swarm agents
$ns at 0.5 “$swarm1 setdest 200 200 10.0”
$ns at 1.0 “$swarm2 setdest 250 250 12.0”
$ns at 1.5 “$swarm3 setdest 300 300 15.0”
$ns at 2.0 “$swarm4 setdest 350 350 18.0”
$ns at 2.5 “$swarm5 setdest 400 400 20.0”
- Run the Simulation
Once the topology, traffic, and mobility are configured, we can execute the simulation.
ns swarm_network.tcl
- Visualize the Simulation
We need to utilize NAM (Network Animator) to envision the swarm movement and communication.
nam swarm_network.nam
- Analyse Simulation Results
The trace file (swarm_network.tr) will contain detailed data on packet transmissions, delays, losses, and other parameters. We can measure the performance of the swarm network by evaluating:
- Throughput: evaluate the data transfer rate among swarm nodes.
- End-to-End Delay: Time taken for messages to travel among nodes.
- Packet Delivery Ratio (PDR): Ratio of successfully delivered packets to the total sent.
- Coordination Efficiency: How efficiently the swarm coordinates according to communication patterns.
Utilize AWK, Python, or Perl scripts to extract key parameters from the trace file.
- Extend the Simulation
11.1 Implement Swarm Algorithms
We can add custom techniques for coordination, task assignment, or formation control. For instance, executing flocking behavior in which robots maintain a formation according to proximity to other swarm members.
11.2 Collaborative Task Execution
Replicate scenarios in which swarm members collaborate to complete tasks such as search and rescue or area coverage.
11.3 Obstacle Avoidance
Incorporate sensor nodes or techniques to replicate real-time obstacle detection and avoidance, a vital part of swarm robotics in dynamic scenarios.
11.4 Energy Efficiency
Replicate energy consumption
In this setup simulation, we had successfully and efficiently replicate the Swarm Networking projects in ns2 environment and provide the elaborated procedures to simulate the execution. Additional specific details regarding the Swarm Networking projects project will be shared in upcoming manual.
