An Efficient WSN Simulator for GPU-Based Node Performance

Abstract

In wireless sensor network, when these sensors are wrongly placed in an observation region, they can quickly run out of batteries or be disconnected. These incidents may result in huge losses in terms of sensing data from numerous sensors and their costs. For this reason, a number of simulators have been developed as tools for effective design and verification before the actual arrangement of sensors. While a number of simulators have been developed, simulation results can be fairly limited and the execution speed can be markedly slow depending on the function of each simulator. In this regard, to improve the performance of existing simulators, this research aimed to develop a parallel calculation simulator for independent sensor (PCSIS) that enables users to selectively use the GPU mode and, based on this mode, enables parallel and independent operations by matching GPU with many cores in order to resolve the slowdown of the execution speed when numerous sensor nodes are used for simulations. The PCSIS supports the GPU mode in an environment that allows the operation of compute unified device architecture (CUDA) and performs the parallel simulation calculation of multiple sensors using the mode within a short period of time.