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This is an implementation of the Granular Neural Network architecture defined by S. Dick, A. Tappenden, C. Badke, O. Olarewaju. It is provided for the use of the public, and the convenience of researchers who may wish to develop or use this new system.
NS-2 Trace Statistics is a tool for easy generation of summary statistics from Network Simulator trace files, such as: total and network delay, packets generated, sent, received and dropped, run length histograms and MRU stack depth.
An implementation of the GSD service discovery protocol for the network simulator ns2 (http://www.isi.edu/nsnam/ns/). The protocol core is written in c++ whereas simulation settings and scenarios can be set up via OTCL scripts -- as usual in ns2.
Design and implementation of the Observation-based Cooperation Enforcement in Mobile Ad-hoc Networks (OCEAN) protocol, on top of the ns2 network simulator, using Dynamic Source Routing (DSR).
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DYMOUM is an implementation of the DYMO (Dynamic Manet On-demand) routing protocol both for Linux kernel and ns2 network simulator, written in C and C++.
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.
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.
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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, ...