How to Implement Large Scale Networks in NS2
To implement the large scale networks in NS2, we have to simulate networks that has large amount of nodes like hundreds or thousands of nodes, while considering scalability threats like memory utilization, CPU time and simulation run-time. These networks are often used for learning the activities of large communication networks like the Internet, data centers or sensor networks in changing conditions. In the offered approach, you can implement the large scale networks using ns2:
To effectively replicate large-scale networks in NS2, you need to concentrate on:
- Efficient node creation and network setup.
- Reducing resource utilization through enhanced routing protocols and careful traffic design.
- Handling memory and computational overhead.
Steps to Implement Large Scale Networks in NS2
- Set Up the NS2 Environment
Make certain that NS2 is installed and set up on a machine with sufficient memory and CPU power to manage large simulations. You might want to execute the simulation on a machine with higher computational resources (such as numerous CPU cores and sufficient RAM) if the network involves thousands of nodes.
- Create a TCL Script for Large Scale Networks
Below is a sample of TCL script that configures a large-scale ad-hoc wireless network with hundreds of nodes. The script is designed to manage the scalability characteristics of node designing, network configuration, and traffic generation.
Example TCL Script for Large Scale Network:
# Create a new NS2 simulator
set ns [new Simulator]
# Open trace and NAM output files
set tracefile [open large_scale.tr w]
$ns trace-all $tracefile
set namfile [open large_scale.nam w]
$ns namtrace-all $namfile
# Define network parameters
set val(chan) Channel/WirelessChannel ;# Wireless channel
set val(prop) Propagation/TwoRayGround ;# Two-ray ground propagation model
set val(ant) Antenna/OmniAntenna ;# Omni-directional antenna
set val(netif) Phy/WirelessPhy ;# Physical layer
set val(mac) Mac/802_11 ;# 802.11 MAC protocol
set val(ifq) Queue/DropTail/PriQueue
set val(ifqlen) 50 ;# Interface queue length
set val(ll) LL
set val(rp) AODV ;# AODV routing protocol for large-scale ad-hoc networks
set val(x) 3000 ;# X-dimension for large network area (meters)
set val(y) 3000 ;# Y-dimension for large network area (meters)
set val(num_nodes) 500 ;# Number of nodes (large-scale network)
# Create topography for large-scale network
set topo [new Topography]
$topo load_flatgrid $val(x) $val(y)
# Configure node parameters for wireless nodes
$ns node-config -adhocRouting $val(rp) \
-llType $val(ll) \
-macType $val(mac) \
-ifqType $val(ifq) \
-ifqLen $val(ifqlen) \
-antType $val(ant) \
-propType $val(prop) \
-phyType $val(netif) \
-channelType $val(chan) \
-topoInstance $topo \
-agentTrace OFF \
-routerTrace OFF \
-macTrace OFF
# Create a large number of nodes and set initial positions randomly
for {set i 0} {$i < $val(num_nodes)} {incr i} {
set node($i) [$ns node]
$node($i) set X_ [expr rand() * $val(x)] ;# Random X position
$node($i) set Y_ [expr rand() * $val(y)] ;# Random Y position
$node($i) set Z_ 0
}
# Create traffic flows between selected nodes
set udp0 [new Agent/UDP]
set udp1 [new Agent/UDP]
set sink0 [new Agent/Null]
set sink1 [new Agent/Null]
# Attach traffic agents to nodes
$ns attach-agent $node(0) $udp0
$ns attach-agent $node(10) $sink0
$ns attach-agent $node(20) $udp1
$ns attach-agent $node(30) $sink1
# Connect agents for communication
$ns connect $udp0 $sink0
$ns connect $udp1 $sink1
# Create CBR traffic for the first UDP connection
set cbr0 [new Application/Traffic/CBR]
$cbr0 set packetSize_ 512 ;# Packet size
$cbr0 set rate_ 1Mb ;# Data rate
$cbr0 attach-agent $udp0
# Create CBR traffic for the second UDP connection
set cbr1 [new Application/Traffic/CBR]
$cbr1 set packetSize_ 512
$cbr1 set rate_ 512Kb
$cbr1 attach-agent $udp1
# Start and stop traffic
$ns at 1.0 “$cbr0 start”
$ns at 2.0 “$cbr1 start”
$ns at 10.0 “$cbr0 stop”
$ns at 12.0 “$cbr1 stop”
# Schedule the simulation end
$ns at 15.0 “finish”
# Define the finish procedure
proc finish {} {
global ns tracefile namfile
$ns flush-trace
close $tracefile
close $namfile
exec nam large_scale.nam &
exit 0
}
# Run the simulation
$ns run
- Explanation of Key Components
- Large Network Area: The simulation area is fix to 3000 x 3000 meters to accommodate a large amount of nodes. The nodes are randomly located within this area.
- Ad-hoc Routing Protocol (AODV): The AODV (Ad-hoc On-demand Distance Vector) routing protocol is used to support multi-hop communication in the large network. Other scalable protocols like DSR or OLSR can also be used.
- Efficient Traffic Setup: Only a few traffic flows are applied to decrease computational load, yet you can extend this to attach more flows if required.
- Trace Options: AgentTrace, RouterTrace, and MacTrace are turned off to minimize the size of the trace file and improve simulation performance, as large-scale simulations can create a lot of data.
- Run the Simulation
store the script as large_scale.tcl and execute the simulation using NS2:
ns large_scale.tcl
After the simulation is done, you can visualize the network using NAM:
nam large_scale.nam
- Analyze the Simulation
In a large-scale simulation, assess the trace file can be complex because its size. Here are some metrics you can extract from the trace file:
- Packet Delivery Ratio (PDR): Compute the ratio of successfully send packets to the total packets sent.
- Throughput: Estimate the total data received at the destination nodes over the simulation time.
- Latency: Measure the end-to-end delay experienced by packets during transmission.
Example: Calculating Throughput Using AWK
Compute throughput from the trace file by using AWK script:
awk ‘/^r/ && /udp/ {sum+=$5} END {print “Throughput: “, sum/15, “bytes/sec”}’ large_scale.tr
This script estimates the total amount of bytes obtained over the entire simulation (15 seconds) and measures the throughput.
- Handling Scalability Challenges
Large-scale networks launch threats like:
- Memory Usage: Replicating thousands of nodes can use a lot of memory. To enhance, turn off non-essential traces and restrict the count of active traffic flows.
- Simulation Time: Executing large simulations can be time-consuming. Consider running simulations in parallel on several machines or using distributed simulation frameworks like NS3 with MPI (Message Passing Interface).
- Optimized Routing Protocols: Ignore overhead allied with routing updates by using scalable routing protocols like OLSR or Fisheye State Routing (FSR) for large-scale networks.
- Extend the Simulation
You can extend the simplified large-scale network simulation in numerous ways:
- a) More Traffic Flows
Imitate a more advanced network by developing more traffic flows amongst different node pairs. For instance, to generate another flow amongst node 50 and node 60:
set udp2 [new Agent/UDP]
set sink2 [new Agent/Null]
$ns attach-agent $node(50) $udp2
$ns attach-agent $node(60) $sink2
$ns connect $udp2 $sink2
set cbr2 [new Application/Traffic/CBR]
$cbr2 set packetSize_ 512
$cbr2 set rate_ 1Mb
$cbr2 attach-agent $udp2
$ns at 3.0 “$cbr2 start”
$ns at 12.0 “$cbr2 stop”
- b) Mobility
Mimic mobile nodes by using the setdest command to travel nodes over time:
# Move node 0 to a new position
$ns at 5.0 “$node(0) setdest 1500 1500 10” ;# Node moves to (1500, 1500) at 10 m/s
- c) Energy Models
Incorporate energy models for large-scale sensor networks to imitate energy utilization and node depletion:
$ns node-config -energyModel EnergyModel -initialEnergy 100.0
- d) Hierarchical Routing Protocols
For extremely large networks, you can use hierarchical routing protocols that break down the network into clusters to decrease routing overhead.
This demonstration completely offers the step-by-step approach to setup the basic network simulation and helps to implement the large scale networks in the ns2 simulation tool by managing scalability challenging. We can also provide the additional details about its optimization, if needed. Dont know How to Implement Large Scale Networks in NS2 tool then you can contact ns2project.com team for tailored assistance.