Most of the existing packet-level simulation tools are designed to perform experiments modeling small to medium scale network nodes. The main reason of this limitation is the amount of available computation power and memory in quasi mono-process simulation environment. To enable efficient packet-level simulation for large scale scenario, we introduce a CPU-GPU co-simulation framework where synchronization and experiment design are performed in CPU and node's logical processes are executed in parallel in GPU according to the master/worker model. The framework is developed using Compute-Unified Device Architecture and denoted as Cunetsim, CUDA network simulator. In this work, we study the node mobility and connectivity as they are among the most time consuming task when large scale network is simulated. Simulation results show that Cunetsim execution time remains stable and that it achieves significantly lower execution time than existing approach when computing mobility and connectivity with no degradation in the accuracy of the results.
Cunetsim: A new simulation framework for large scale
SIMUTOOLS 2012, 5th International Conference on Simulation Tools and Techniques, March 19-23, 2012, Desenzano, Italy
Poster / Demo
© ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in SIMUTOOLS 2012, 5th International Conference on Simulation Tools and Techniques, March 19-23, 2012, Desenzano, Italy
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