Abstract:

Due to the computationally-intensive characteristic, the available radio channel simulators of wireless sensor networks (WSN) cannot achieve efficient execution performances. A parallel radio channel simulator using Nvidias graphics processing unit + compute unified device architecture (GPU+CUDA) parallel computing architecture is proposed. Firstly, CUDA-trees is developed, which can reside on the fast on-chip memory of GPU, so as to organize sensor nodes and facilitate detection of possible transmitters in simulation. Secondly, a CUDA parallel radio channel simulating engine is established, which is totally different from that in traditional WSN simulators. Experiments show that this simulating system greatly outperforms a central processing unit implementation with an up to 528.73 times speedup and has a linear scalability.

Key words: wireless sensor networks, radio channel, simulation, compute unified device architecture-trees