STARS: A Framework for Statistically Rigorous Simulation-Based Network Research

Abstract

Simulation has become one of the dominant tools in wired and wireless network research. With the advent of cloud, grid, and cluster computing it has become feasible to use parallelization to perform richer larger-scale simulations. Moreover, the computing resources needed to perform statistically rigorous simulations are now easily obtainable. Although a number of parallel network simulation frameworks exists, the issue of statistical rigorous testing has largely not been addressed. This work presents a parallel MPI-aware network simulation framework that is specifically designed to provide automated support for statistically rigorous experimentation, thereby offloading this significant researcher burden. Unlike prior frameworks, the proposed framework includes a distribution-free statistical analysis feedback loop that automatically deduces the next set of experiments that need to be run. The value of this new framework is highlighted by exploring the well known issue of assessing the true duration of start-up transients within mobile ad hoc networks (MANETs) simulations.