Assistance for Simulations and Analysis of Industrial as well as Scholarly Research works
Installing ‘lorawan’ extension module version v0.3.1 under ns-3.42
LoRaWAN The LoRa Alliance first defined the LoRaWAN standard with the objective of creating a medium access scheme and a set of network management policies that leverage the properties of […]
Simulation and Analysis of IoT LoRaWAN Networks Under ns-3
Low-power wide-area network (LPWAN). These networks use low-power radio signals, such as those in the sub-1 GHz range, to send small amounts of data over a large area. LPWANs are […]
Creating Random Road Network, Traffic Flows, Signals in SUMO
SUMO has different tools for creating and customizing road networks and traffic flows and traffic signals. In this article, we will use some of those tools available in SUMO to […]
Implementation of Spring Mobility Model for ns-3 and Visualizing it in 3D along with Circle Mobility
Spring Mobility Spring mobility is nothing but making a node to move in a path similar to that of an expanded circular coil spring. From the top or bottom point […]
Implementation of Circle Mobility Model for ns-3 and Visualizing it in 3D
Mobility Models of ns-3. The default ns-3 installation will contain the following mobility models. MobilityModel Subclasses ConstantPosition ConstantVelocity ConstantAcceleration GaussMarkov Hierarchical RandomDirection2D RandomWalk2D RandomWaypoint SteadyStateRandomWaypoint Waypoint PositionAllocator Position allocators […]
3D Aquatic Animal Tracking Underwater Network Simulation (UWSN) Under ns-3
Aquatic Animal Tracking: Tracking marine animals can be extremely tricky due to GPS signals not functioning well underwater[1]. Underwater acoustic communication is a technique of sending and receiving messages below […]
Visual Studio Code (VS Code) is an open-source source-code editor made by Microsoft for Windows, Linux and macOS[1]. It has the support for debugging, syntax highlighting, intelligent code completion, snippets, […]
Low-power wide-area network (LPWAN). These networks use low-power radio signals, such as those in the sub-1 GHz range, to send small amounts of data over a large area. LPWANs are […]
Forward Erasure Correction (FEC) Packet-level forward erasure correction is effective for achieving low-latency transmissions in non-terrestrial networks (NTNs), which often contain lossy links with long propagation delay[1]. In [1] the […]
Even though I am not civilized enough to say “wish messages” to people, let me try to deliver a “Happy New Year” wish message to the members of ns-3 user […]
SRCM – Semi Random Circular Mobility Model of ns-3 While trying to raise my own merge request for my Simple Circle Mobility Model, on GitLab, I saw another merge request […]
In this post, I want to share my first experience on ‘Raising a simple merge request at GitLab’ at https://gitlab.com/nsnam/ns-3-dev/-/merge_requests You may find that specific request at – A Simple CircleMobilityModel […]
For a very long time, I wish to contribute my own little things to ns-3. But whenever I read the guide on contributing to ns-3, I could not able to understand […]
Contention Window Optimization. The proper setting of contention window (CW) values has a significant impact on the efficiency of Wi-Fi networks. Unfortunately, the standard method used by 802.11 networks is […]
ndnSIM: Named-Data Networking (NDN) Simulator. ndnSIM is an ns-3 module to enable experimentation with Named-Data Networking (NDN). It is an open-source ns-3 module that enables experimentation with the Named-Data Networking […]
I started to discuss problems in understanding ns-3 in the article “What Makes ns-3 a Complex Thing to Understand and Use? “. I received answers and valuable comments from the ns-3 […]
Millicar is an ns-3 module for the simulation of Vehicle-to-Vehicle networks operating at mmWaves[2]. It was developed by SIGNET Lab, University of Padova. The following figure from [1] shows the […]
While starting to learn ns-3, most of us find it very difficult to understand. Particularly, if the student is already familiar with ns-2 or Omnet++ then it will even become […]
ns3-gym is the first framework for RL research in networking[4]. It is based on OpenAI Gym, a toolkit for RL research and ns-3 network simulator. Specifically, it allows representing an […]
Simulation of Simple 3D FANET with TCP flows under ns-3 In this example, we simulate TCP flows in a FANET scenario, but the same idea can be implemented on a […]
If we want to implement AI algorithms in our custom network protocol/application under ns-3, then the direct way is to incorporate an existing AI/ML/DL framework with it. If it will […]