Red Hat Ansible Automation Platform on Microsoft Azure
Red Hat Ansible Automation Platform on Azure allows you to quickly deploy, automate, and manage resources securely and at scale.
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User mode linux virtual machines management in pure bash 3.x Manages separate hosts and virtual networking on linux host, firewalling planned. This tool aims to be lightweight production environment controler, not a huge virtual network simulator.
Cervelletto is a neural network simulator. It uses a new neural model based on biological, neurological and psychological studies. [it's not yet completed... just give me some weeks! sorry!]
DSR-UU is an implementation of the Dynamic Source Routing protocol that runs in the Linux kernel or in the ns-2 network simulator. It was originally created at Uppsala University, hence the UU.
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QUENAS (QUeued Event Network Automatic Simulator) is a Network Simulator that enables to create a network of nodes and simulate communications between then. Currently, the Hypercube protocol is implemented at network layer.
A network simulator written in flash. Build up a topolog and send packets throught your network, see and inspect them as they travel, change the headers and observe such protocols as ARP and switch learning.
The NS-Mapper ad-hoc scenario editor is improved and extended by adding more realistic strategies, such as random based node placement, movement and traffic to the ad-hoc simulation of the Network Simulator 2 (NS-2).
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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.
iSNS is an interactive neural network simulator written in Java/Java3D. The program is intended to be used in lessons of Neural Networks. The program was developed by students as the software project at Charles University in Prague.
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.
The goal of this project is to be an improvement of the original Network Animator (NAM) module provided as part of the Network Simulator 2 (NS2). This tool provides topology visualization, TCL script generation, and enhanced simulation animation.
rsim is a simple discrete-event communications network simulator initially developed to test routing protocols for undersea acoustic modem networks. If done well then rsim will eventually be a good replacement for "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).
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.
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.