Search Results for "c for windows 8"

The Common Open Research Emulator (CORE) is a tool for emulating networks on one or more machines. You can connect these emulated networks to live networks. CORE consists of a GUI for drawing topologies of lightweight virtual machines, and Python modules for scripting network emulation.

This is a basic implementation of an Information-Centric Network simulator, following the architecture suggested by Blackadder. It was by the University of Essex for the needs of the PAL project and it include Publishers, Subscribers, RV and a Topology Manager.

AHANNS enables the user to create and train artificial neural networks. Training is carried out by an implementation of back propagation learning algorithm. See the documentation for details. This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be...

VisualVNC is a connector between virtual network and physical network. A virtual network mainly refers to the topology created by GNS3 (Graphical Network Simulator, a popular network simulator), the physical network means the real machines or virtual machines (created by VMware, virtualbox and so on) which are running Windows.

UM-OLSR is an OLSR (Optimized Link State Routing protocol) implementation for the ns2 network simulator.

Simured is a multicomputer network simulation whith visual interface to see packet movement on the network. It is multi platform and there are versions in Java and C++.

NeMo is a high-performance spiking neural network simulator which simulates networks of Izhikevich neurons on CUDA-enabled GPUs. NeMo is a C++ class library, with additional interfaces for pure C, Python, and Matlab.

This project is based on a personal effort for researches on dynamics of coevovling networks. As a physicist, I am trying to build a framework for discrete-time dynamics of general networks, and its software libraries with APIs.

This project provides an OSPF implementation for the Network Simulator 2 (ns-2).

Datagram Congestion Control Protocol (DCCP) for Network Simulator.

AWNetS(Aibear Wireless Network Simulator)is a C++ written,fire-new discrete-event wireless network simulator which integrates network and communication simulations.It also focuses on various kinds of wireless networks including satellite and HAP.

Yans is a extensible, mixed-level, Monte-Carlo Method based, discrete event network simulator. Yans is divided into interacting layers, namely: core, topology, nodes, monitors; and is driven by a config-file that describes the setup of the network.

Mangrovia is a tool for automatic complex multilayer topology generation in a compatible format with Network Simulator 2 (ns-2). Based on specs (in xml format), software creates an otcl script. Users can set Bandwidths, Distances, Linking Policies.

This projects goal is to develop a WiMAX module for the NS-MIRACLE library for the network simulator NS-2.

OPENOLSRV2 is an OLSRv2 (Optimized Link State Routing protocol version 2) implementation for the ns2 network simulator.

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.

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

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.

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.