Simulation has been an important resource for functional and performance analyses of computer networks. Although the number of widely adopted network simulators is small, new ones continue to be created to address gaps in the functionality of existing tools. It can be argued, however, that the greatest need of the scientific community is to raise the credibility of published simulation studies. In this paper, we show that this need can be addressed by enabling network simulators to provide fool-proof automation of the experimental process. Ideally, the simulator's interface would provide users with an environment to minimize set up time for experiments and to guarantee their reproducibility, and to safeguard the statistical rigor of data analysis. We demonstrate that advances toward this goal have been made by three different tools. Our contributions in this paper culminate with the derivation of requirements for automation tools from recent literature and from our own experience in tool construction. Once these requirements are fulfilled, network simulation tools can have a stronger impact in education, in carrying out large simulation studies, and in enhancing the credibility of simulation results.

On The Automation of Computer Network Simulators

CICCONETTI, CLAUDIO;STEA, GIOVANNI;
2009-01-01

Abstract

Simulation has been an important resource for functional and performance analyses of computer networks. Although the number of widely adopted network simulators is small, new ones continue to be created to address gaps in the functionality of existing tools. It can be argued, however, that the greatest need of the scientific community is to raise the credibility of published simulation studies. In this paper, we show that this need can be addressed by enabling network simulators to provide fool-proof automation of the experimental process. Ideally, the simulator's interface would provide users with an environment to minimize set up time for experiments and to guarantee their reproducibility, and to safeguard the statistical rigor of data analysis. We demonstrate that advances toward this goal have been made by three different tools. Our contributions in this paper culminate with the derivation of requirements for automation tools from recent literature and from our own experience in tool construction. Once these requirements are fulfilled, network simulation tools can have a stronger impact in education, in carrying out large simulation studies, and in enhancing the credibility of simulation results.
2009
9789639799455
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/131237
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