CUDA accelerated large scale vehicular area network simulator

Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer ScienceBoth size and computational activities of Vehicular Area Network (VANET) are growing. Simulation of VANETs not only requires the simulation of network standards, but also the mobility of nodes. Such dynamic system involves computation of node distance, routing protocols, application layer, data send, data receive, etc. The simulation model of VANET requires both hardware and software support to deal with massive computational problems. Currently available network simulators, like network simulator 3 (NS-3), are not adequate for simulating large-scale VANET systems. In this work, we propose a dual-stream Compute Unified Device Architecture (CUDA)-assisted VANET simulation model for multicore Central Processing Unit (CPU) / manycore Graphics Processing Unit (GPU) platform to increase computational throughput. The proposed CUDA assisted VANET simulator uses NS-3 as the core engine and improves throughput by exploiting massively parallel processing on the GPU. Experimental results show that the computation throughput can be increased up to 75x by splitting workload between CPU and GPU