Genetic Algorithm Implementation in ns2

Genetic Algorithm Implementation in ns2

Genetic Algorithm is designed to simulate processes in natural systems. Over a consecutive generation, GA stimulates the survival of the fittest among individuals. GA is also a part of evolutionary computing. We guide research scholars for genetic algorithm implementation in ns2 simulator with source code.

Basic Operators in GA

   After the initial population, the algorithms define the following functions

  • Selection.
  • Crossover.
  • And also Mutation.

   Get to know about the basic operator, applications, and benefits of genetic algorithm projects. Implement genetic algorithm in ns2 with guidance from industry experts for an affordable cost.

Implementing genetic algorithm in ns2 using stochastic search algorithm

Applications of GA

  • Airlines Revenue Management.
  • Artificial creativity.
  • Biology and also computational chemistry.
  • Chemical kinetics.
  • Computer architecture.
  • Clustering.
  • Electronic circuit design.
  • Economics.
  • Image processing.
  • Mechanical engineering.

Benefits of GA

  • GA solves the optimization problem.
  • Solves problems with multiple solutions.
  • Its execution technique is not dependent on the error surface.
  • A structural genetic algorithm gives the possibility to solve the solution structure.
  • The GA method is very easy to understand.
  • Easily transferred to existing simulations and also models.

Genetic Algorithm Implementation in ns2 helps to solve out

  • Multi-dimensional.
  • Non-differential.
  • Non-continuous.
  • And also in Non-parametrical problems.

Sample code for genetic algorithm implementation in ns2

#Creating a new Simulator object

set ns [new Simulator]

#Opening file to be used as nam trace file

set nf [open shot.nam w]

$ns namtrace-all $nf

#Finish procedure

proc finish {} {

global ns nf

$ns flush-trace

close $nf

exec nam shot.nam &

exit 0}

#Defining two nodes

set n0 [$ns node]

set n1 [$ns node]

#Connecting two nodes

$ns duplex-link $n0 $n1 1Mb 10ms DropTail

#CreateUDP agent and connect to node0

set udp0 [new Agent/UDP]

$ns attach-agent $n0 $udp0

#Create CBR traffic source and attach to UDP agent

set cbr0 [new Application/Traffic/CBR]

$cbr0 set packetSize_ 500

$cbr0 set interval_ 1

$cbr0 attach-agent $udp0

set null0 [new Agent/Null]

$ns attach-agent $n1 $null0

$ns connect $udp0 $null0

#CreateUDP agent and connect to node1

set udp1 [new Agent/UDP]

$ns attach-agent $n1 $udp1

#Create CBR traffic source and attach to UDP agent

set cbr1 [new Application/Traffic/CBR]

$cbr1 set packetSize_ 500

$cbr1 set interval_ 1

$cbr1 attach-agent $udp1

set null1 [new Agent/Null]

$ns attach-agent $n0 $null1

$ns connect $udp1 $null1

for {set i 0} {$i < 10} {incr i} {

set q [expr $i%2]

if {$q==0} {

set a i

set b [expr $i+1]

$ns at a “$cbr0 start”

$ns at b “$cbr0 stop”}

if {$q!=0} {

set a i

set b [expr $i+1]

$ns at a “$cbr1 start”

$ns at b “$cbr1 stop”}}

#Stop after 10 seconds

$ns at 10.0 “finish”

Running simulation

$ns run

Live Tasks
Technology Ph.D MS M.Tech
NS2 75 117 95
NS3 98 119 206
OMNET++ 103 95 87
OPNET 36 64 89
QULANET 30 76 60
MININET 71 62 74
MATLAB 96 185 180
LTESIM 38 32 16
COOJA SIMULATOR 35 67 28
CONTIKI OS 42 36 29
GNS3 35 89 14
NETSIM 35 11 21
EVE-NG 4 8 9
TRANS 9 5 4
PEERSIM 8 8 12
GLOMOSIM 6 10 6
RTOOL 13 15 8
KATHARA SHADOW 9 8 9
VNX and VNUML 8 7 8
WISTAR 9 9 8
CNET 6 8 4
ESCAPE 8 7 9
NETMIRAGE 7 11 7
BOSON NETSIM 6 8 9
VIRL 9 9 8
CISCO PACKET TRACER 7 7 10
SWAN 9 19 5
JAVASIM 40 68 69
SSFNET 7 9 8
TOSSIM 5 7 4
PSIM 7 8 6
PETRI NET 4 6 4
ONESIM 5 10 5
OPTISYSTEM 32 64 24
DIVERT 4 9 8
TINY OS 19 27 17
TRANS 7 8 6
OPENPANA 8 9 9
SECURE CRT 7 8 7
EXTENDSIM 6 7 5
CONSELF 7 19 6
ARENA 5 12 9
VENSIM 8 10 7
MARIONNET 5 7 9
NETKIT 6 8 7
GEOIP 9 17 8
REAL 7 5 5
NEST 5 10 9
PTOLEMY 7 8 4

Workflow

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Unlimited Network Simulation Results available here.