TraceMetrics is a trace file analyzer for Network Simulator 3 (ns-3).
TraceMetrics is a trace file analyzer for Network Simulator 3 (ns-3). The main goal is to perform a quick analyzis of the trace file produced by ns-3's simulations and calculate useful metrics for research and performance measurement.
Such tool is needed because a research simulation may generate a trace file with thousands of lines, becoming dificult to analyze manually. Due to this, this tool can be handy in case someone needs a metric that the tool already support.
TraceMetrics is...
Positioning Algorithms for Mobile Ad Hoc Networks.
The DV-Hop, Amorphous, Centroid and APIT sourcecode 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.
This is a network simulator. This is meant to be user friendly as well as feature rich. This field lacks software with good user interface. Even the commercial softwares in this field is quite lame. This aimed to go along Multisim(R) and Blender(R) form
Main sourcecode 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.
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.