Automating Large-Scale Simulation and Data Analysis with OMNeT++: Lession Learned and Future Perspectives

نویسندگان

  • Antonio Virdis
  • Carlo Vallati
  • Giovanni Nardini
چکیده

Simulation is widely adopted in the study of modern computer networks. In this context, OMNeT++ provides a set of very effective tools that span from the definition of the network, to the automation of simulation execution and quick result representation. However, as network models become more and more complex to cope with the evolution of network systems, the amount of simulation factors, the number of simulated nodes and the size of results grow consequently, leading to simulations with larger scale. In this work, we perform a critical analysis of the tools provided by OMNeT++ in case of such large-scale simulations. We then propose a unified and flexible software architecture to support simulation automation. Keywords—OMNeT++; Large-Scale Simulations; Data Analysis; Simulation automation

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عنوان ژورنال:
  • CoRR

دوره abs/1609.04603  شماره 

صفحات  -

تاریخ انتشار 2016