The Network Simulator 2 (ns-2) is an open source tool for network simulation. When planning for large-scale simulation experiments, an efficient and flexible data collection and a statistically sound output data analysis are important aspects to keep in mind. Unfortunately, ns-2 offers little support for data collection, and statistical analysis of the simulation results is most often performed offline, using either home made code or available packages, which are not integrated with ns-2. In this paper we describe two complementary contributions: the first one consists of a set of C++ modules, that allow a flexible and efficient data collection; the second one is a software framework, which is fully integrated with ns-2, that performs all the operations required to carry out simulation experiments in a statistically sound way. Our framework allows a user to significantly reduce the postprocessing overhead and to save simulation time, especially with large-scale simulations. Our code is publicly available at [3].

An Integrated Framework for Enabling Effective Data Collection and Statistical Analysis with ns-2

CICCONETTI, CLAUDIO;MINGOZZI, ENZO;STEA, GIOVANNI
2006-01-01

Abstract

The Network Simulator 2 (ns-2) is an open source tool for network simulation. When planning for large-scale simulation experiments, an efficient and flexible data collection and a statistically sound output data analysis are important aspects to keep in mind. Unfortunately, ns-2 offers little support for data collection, and statistical analysis of the simulation results is most often performed offline, using either home made code or available packages, which are not integrated with ns-2. In this paper we describe two complementary contributions: the first one consists of a set of C++ modules, that allow a flexible and efficient data collection; the second one is a software framework, which is fully integrated with ns-2, that performs all the operations required to carry out simulation experiments in a statistically sound way. Our framework allows a user to significantly reduce the postprocessing overhead and to save simulation time, especially with large-scale simulations. Our code is publicly available at [3].
2006
1595935088
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/187425
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