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The aim of this project is to have a current implementation of the experimental VFER protocol (http://vfer.sf.net) within the ns-2 network simulator. The design of VFER can then be tweaked using results from this simulation.

This project provides DiffServ simulations improvements for the Network Simulator 2. The current version works for NS2 version 2.29

NS2 Linux is dedicated to improve the Network Simulator (NS-2) to match Linux performance. Planned contents include: an NS-2 module that runs Linux congestion control functions, tutorials on how to run NS-2 to match Linux performance, benchmark for TCP.

SNNSraster is a utility for quick ANN analysis of raster GIS maps with the use of Stuttgart Neural Network Simulator trained network files. It was developed to read and write binary raster files. SNNSraster is a project of the Geography Laboratory of the University of Siena. The code was developed by Giancarlo Macchi Jánica between 2006 and 2007. SNNSraster's fundamental objective is to improve the ability to integrate the use of artificial neural networks in GIS environments.

A modern and usable interface for the well known neuronal network simulator SNNS. The GUI acts as a client to serveral servers embedding SNNS and supports team work aspects.

ROOTSNNS is a set of C++ classes which allows one to use the Stuttgart Neural Network Simulator kernel (ansi-C) within the ROOT, a data analysis package. Multiple ANNs can be built, trained, and tested, while results and ANN performance can be saved.

WIPsim (Wireless IP Simulator) is a network simulator for all layers of the OSI model. The current version is focussed on dealing with IPv6. The simulator was started to investigate wireless (data) networks and mobility.

GNNS - GNNS Neural Network Simulator, is both a set of libraries and an interface for creating and learning neural networks. It is aimed to support as many network typs and learning algorithms as possible. GNNS is meant to support different platforms.

RooCARDS is a set of C++ classes written for the ROOT analysis framework which interface ROOT to the Stuttgart Neural Network Simulator (SNNS). This interface is based on a concept originally developed by Professor Yibin Pan at the UW-Madison.

bns is a network simulator. You can create a complete network, add services to host, ... It can be usefull to study network behavior, make presentations, learn hacking techniques, ...