Research of WSNS coverage in coal mine based on GNG-Like intelligent algorithm

Coverage in wireless sensor networks (WSNs) is treated as a key technology for many monitoring applications. A novel sensor node´s model is presented based on the neural network because the exiting models are not feasible in the special coal mine environment. In addition, we provide an improved intelligent algorithm GNG-Like(Growing Neural Gas-Like), taking into consideration application-special requirements and energy-conservation characteristics, which is applied into the coal mine to study the dynamic coverage in the inspection field. In GNG-Like, threshold is set and corresponding parameters are modified to achieve fast response and coverage for the changing environment in coal mine. We simulate GNG-Like algorithm in the Java platform and compare it to GNG intelligent algorithm. Simulation results show that, compared with the exiting GNG, GNG Like has a faster reaction rate, achieves optimize dynamic coverage and prolongs the network lifetime.