Skip to main content


Showing posts from November, 2020

PyTorch Code for Simple Neural Networks for MNIST Dataset

Flying Adhoc Network Simulation (FANET) using NS3

In this post, we will see how to simulation a Flying Adhoc Network (FANET) simulation using NS3.  Its actually MANET with 3D mobility Model called Gauss Markov Mobility Model.  See the following video for more details and explanation: So all the nodes are flying in a 3D Fashion with X axis, Y Axis and Z Axis  The default values of the three axes are  X axis can be (-100m, 100m) Y axis can be (-100m, 100m) Z axis can be (0m, 100m) We will take the following example for experimenting the Flying Adhoc Networks. To begin with, We use the following parameters for Simulation: The name of the File is #include "ns3/point-to-point-module.h" #include "ns3/ipv4-global-routing-helper.h" #include <fstream> #include <string> #include "ns3/core-module.h" #include "ns3/network-module.h" #include "ns3/applications-module.h" #include "ns3/mobility-module.h" #include "ns3/config-store-module.h" #include &quo

Installing NS-3.31 in Ubuntu 20.04

Installing ns-3.31 in Ubuntu 20.04 - 64 bit OS. Follow the full video for more details: Fresh installation of Ubuntu OS  $] sudo apt update $] sudo apt install build-essential autoconf automake libxmu-dev $] sudo apt install build-essential autoconf automake libxmu-dev python-pygraphviz cvs mercurial bzr git cmake p7zip-full python-matplotlib python-tk python-dev python-kiwi python-gnome2 python-gnome2-desktop qt4-dev-tools qt4-qmake qt4-qmake qt4-default gnuplot-x11 wireshark extract to /home/pradeepkumar $] echo $HOME $] cd ns-allinone-3.31/ $] ./ --enable-examples --enable-tests you will get the following screen after the installation $] cd ns-allinone-3.31/ns-3.31/ $] ./waf --run hello-simulator  This will display  "Hello Simulator"  Which indicates that ns3 is installed successfully. $] ./waf --run first