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Installing ns-3.37 and ns-3.35 in Ubuntu | Ubuntu 22.04 | NS3

Multiple Versions of ns3 in Ubuntu 22.04 In this post, we are going to install two versions of ns3 namely ns-3.35 and ns-3.37  My OS is : Ubuntu 22.04 LTS (Long Term Support) ns-3.35 uses waf and (./waf --run scratch/first)  ns-3.37 uses cmake  (./ns3 run scratch/first.cc) So we will install both the packages  Go through the video for complete instructions To start with  $ sudo apt update  $ sudo apt install build-essential autoconf automake libxmu-dev g++ python3 python3-dev pkg-config sqlite3 cmake python3-setuptools git qtbase5-dev qtchooser qt5-qmake qtbase5-dev-tools gir1.2-goocanvas-2.0 python3-gi python3-gi-cairo python3-pygraphviz gir1.2-gtk-3.0 ipython3 openmpi-bin openmpi-common openmpi-doc libopenmpi-dev autoconf cvs bzr unrar gsl-bin libgsl-dev libgslcblas0 wireshark tcpdump sqlite sqlite3 libsqlite3-dev  libxml2 libxml2-dev libc6-dev libc6-dev-i386 libclang-dev llvm-dev automake python3-pip libxml2 libxml2-dev libboost-all-dev  I have downloaded both the versions of ns3 fr

Random Number Generation using ns2

Random variables is an important concept in networks as the modeling of network traffic and other packet arrival times are mostly random models. Hence there is a necessity of modeling such metrics in ns2. NS2 supports various random models using different seed generations.

Seeds are numbers that are helpful in generating the random numbers. The seed number 0 indicates that the random number order changes every time the simulation is running. But other than 0, the order in which the random number generated are same.


The following listing 1 shows the random number generation for various distributions. This listing will just tell you how to create random number generation for various distributions. For seeing the output, refer to listing 2

Listing 1 – Random Number Generation Sample
#create the random number generation using RNG
set rand1 [new RNG]
set rand2 [new RNG]
set rand3 [new RNG]
#$repli is the value set already and it can be either 1 or <1 or >1
for {set i 1} {$i < $repli} {incr i} {
$rand1 next-substream;
$rand2 next-substream;
$rand3 next-substream;
}

Here are the distributions
Pareto Distribution
set r1 [new RandomVariable/Pareto]
$r1 use-rng $rand1
$r1 set avg_ 10.0
$r1 set shape_ 1.2

Constant – Specifies the constant number
set r2 [new RandomVariable/Constant]
$r2 use-rng $rand2
$r2 set val_ 5.0

Uniform distribution – Specifies the min and max number
set r3 [new RandomVariable/Uniform]
$r3 use-rng $rand3
$r3 set min_ 0.0
$r3 set max_ 10.0

Exponential distribution.- Specified the average value:
set r4 [new RandomVariable/Exponential]
$r4 use-rng $rand1
$r4 set avg_ 5

Hyperexponential distribution
set r5 [new RandomVariable/HyperExponential]
$r5 use-rng $rand2
$r5 set avg_ 1.0
$r5 set cov_ 4.0


The following listing 2 creates the random number generation for two different distributions uniform and exponential. The replication number is supplied through the command line option. If no replication number is supplied, it will be taken as 0 and it a value less than 1 is supplied then, it will be running with value 1. So the following example uses the replication number as 0, 1 or any higher number > 1 and it uses a seed value of 9999
The syntax for setting the seed value is

$defaultRNG seed N

Where N is a interger which may take 0 or 1 or any positive number

Listing 2 – Random number generation – Case 1
#filename : randtest1.tcl
#
# Usage: ns randtest.tcl [replication number]
#

if {$argc > 1} {
    puts "Usage: ns randtest1.tcl \[replication number\]"
    exit
}
set run 1
if {$argc == 1} {
    set run [lindex $argv 0]
}
if {$run < 1} {
    set run 1
}

# seed the default RNG
global defaultRNG
$defaultRNG seed 9999

# create the RNGs and set them to the correct substream
set arrivaldist [new RNG]
set size [new RNG]
for {set j 1} {$j < $run} {incr j} {
    $arrivaldist next-substream
    $size next-substream
}

# arrival_ is a exponential random variable describing the time between
# consecutive packet arrivals
set arrival_ [new RandomVariable/Exponential]
$arrival_ set avg_ 5
$arrival_ use-rng $arrivaldist

# size_ is a uniform random variable describing packet sizes
set size_ [new RandomVariable/Uniform]
$size_ set min_ 100
$size_ set max_ 5000
$size_ use-rng $size

# print the first 5 arrival times and sizes
for {set j 0} {$j < 5} {incr j} {
    puts [format "%-8.3f  %-4d" [$arrival_ value] \
            [expr round([$size_ value])]]
}
Here is the sample output for above file
Prompt] ~/ns-allinone-2.35/ns-2.35/tcl/ex $ ns randtest1.tcl 0
6.358     4783
5.828     1732
1.469     2188
0.732     3076
4.002     626
Prompt]~/ns-allinone-2.35/ns-2.35/tcl/ex $ ns randtest1.tcl 1
6.358     4783
5.828     1732
1.469     2188
0.732     3076
4.002     626
Prompt]~/ns-allinone-2.35/ns-2.35/tcl/ex $ ns randtest1.tcl 2
2.091     153
12.085    4732
3.588     2329
1.201     230
5.161     2980
Prompt]~/ns-allinone-2.35/ns-2.35/tcl/ex $ ns randtest1.tcl 3
2.515     1119
3.154     3118
9.673     1201
13.346    2515
7.052     2115
Prompt]~/ns-allinone-2.35/ns-2.35/tcl/ex $ ns randtest1.tcl 100
8.940     2149
0.888     4870
0.998     4860
1.801     1205
18.224    2534
Prompt]~/ns-allinone-2.35/ns-2.35/tcl/ex $ ns randtest1.tcl 0.5
6.358     4783
5.828     1732
1.469     2188
0.732     3076
4.002     626



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