Open Source Network Simulators - Page 3

QoE Monitor is an open-source software module for Network Simulator 3 (NS-3), usable to perform Quality-of-Experience (QoE) evaluations of multimedia communications in simulative networks. More in detail, it is able to assess the user perceived quality of audio and/or video multimedia streams. Its design has been inspired by EvalVid (link to http://www.tkn.tu-berlin.de/menue/research/evalvid/). QoE Monitor is currently developed by the Networking Research group of University of Modena and Reggio Emilia (http://www.unimore.it/). List of currently available features: - PSNR/SSIM computation for H.264 video transmission - G.711 audio transmission - Basic RTP emulation - Receiver side jitter estimation, according to RFC 3550 To do: - support new audio and video codecs - support new audio and video formats - develop objective audio evaluation metric(s) Update 02/27/2013: The latest archive has been updated to include some new features.

The goal of the Narses project is to build a scalable, application-level network simulator that allows experimenters to use network models of varying degrees of accuracy and speed to efficiently simulate large distributed applications.

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 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.

Network simulation for OSI layers in order to study computer network

This is a application for simula Neuronals Networks, now only support the Backpropagation Network. In the future maybe support ART, Adaline, Madaline, and other Neuronal Networks. Use gnuplot to draw the lms error.

NsGraph is a graphic user interface for modelling and automated generation of scripts for Network Simulator.

tlearn is a backpropagation neural network simulator, written by Jeff Elman. xtlearn is a version of tlearn for the X Window System. OSXtlearn is xtlearn wrapped in a MacOSX application bundle that runs ons MacOSX 10.5 or higher and that requires XQuartz. OSXtlearn is created by Harm Brouwer.

A Java neural network simulator for a type of new spiking neuron model. More information will be available later.

Main source code is moved at https://github.com/jpahullo/planetsim. We recommend authors of contributions sections to move your code to github. Since then, contributions remain here for your use at will. PlanetSim is an object oriented simulation framework for overlay networks and services. This framework presents a layered and modular architecture with well defined hotspots documented using classical design patterns.

The NCTUns is a network simulator and emulator. Each version adheres to only a selected GNU/Linux distribution of fedora (The latest NCTUns 6.0 adhering to fedora 12). We try to port the latest NCTUns 6.0 to Ubuntu 10.04 or later versions.

The DV-Hop, Amorphous, Centroid and APIT source code for NS2. Please reference this work as follows: A. Pineda-Briseño, R. Menchaca-Mendez, E. Chavez, G. Guzman, R. Menchaca-Mendez, R. Quintero, M. Torres, M. Moreno, and J. L. Diaz-De-Leon. "A Probabilistic Approach to Location Estimation in MANETs." Ad Hoc & Sensor Wireless Networks, vol. 28, no. 1-2, pp. 97-114, 2015.

A wireless push-type network simulator that considers locality of demand for performance improvement. The network environment consists of multiple directed emitters for parallel data broadcasting. Performance depends on the mean response time of clients.

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 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.

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.

SGsim is a co-simulation framework consists mainly of the network simulator OMNeT++ and the power grid simulator OpenDSS. Related Publications: Abdalkarim Awad, Peter Bazan and Reinhard German, " A Short Tutorial On Using SGsim Framework For Smart Grid Applications" Proceedings of the 10th EAI on Performance Evaluation Methodologies and Tools 2016, Taormina, Italy, pp.1-6, October 2016 Abdalkarim Awad, Peter Bazan and Reinhard German, " Co-Simulation-Based Evaluation of Volt-VAR Control," IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), Ljubljana, Slovenia, pp. 1-6, October 2016 Abdalkarim Awad, Peter Bazan and Reinhard German, "SGsim: Co-Simulation Framework for ICT-Enabled Power Distribution Grids," (MMB & DFT 2016), Münster, Germany, pp. 5-8, April 2016 Abdalkarim Awad, Peter Bazan and Reinhard German, "SGsim: a Simulation Framework for Smart Grid Applications," Proceedings of the IEEE International Energy Conference (ENERGYCON 2014), Dubrovnik, Croatia.

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.

SVCEval-RA is a simulation framework for rate-adaptive video transmission using the Scalable Video Coding standard (H.264/SVC). Our approach uses feedback information about the available bandwidth to allow the video source to select the most suitable combination of SVC layers for the transmission of the video sequence. The proposed solution has been integrated into the network simulator NS-2 in order to support realistic network simulations.

SW2SPA is an educational simulator with animation for network protocols that allow reliable data transfer, specifically developed for the stop and wait protocols, go-back-N and selective repeat. The aim of SW2PSA is to be used as a tool to support the animation of this protocols in a course like data networks, communication protocols or other related, and to include in the course a project that involves the programming of any of these protocols using a very known language as Java. Since it is an open source program also helps the student who wishes to know the structure of a simple discrete event network simulator.

Deploys a secure VPC on AWS with public/private subnets using Terraform. This tool provides a calculator and generator for AWS VPC Terraform configurations. It allows you to quickly scaffold a secure VPC with multiple subnets. Quick Start To use this tool, run the generator: bash # Generate a VPC with 3 subnets python lab_runner.py vpc-gen --cidr 10.10.0.0/16 --subnets 3 --output my_vpc.tf

Improved Network Energy Conserving Algorithm based Sensor Network Simulator. The algorithm derives from LEACH and gives better performance.

An adhoc network simulator that tests multiple transceiver base stations in a peer to peer environment.

The program Virtual Network Simulator for Web 2.0 is a tool that allows the simulation of assembly and configuration of computer network projects, virtual or physical. It also simulate the sending of a package between the hots of origin and destinati