earticle

영어

Energy efficiency is the primary goal of wireless sensor network. An energy conversion model in wireless sensor network node’s different state is established by an analysis of energy consumption of wireless sensor network, node composition and working state, considering the wireless sensor network node’s working condition and the other nodes’ data acquisition, transmission and other factors within the wireless sensor network. Optimized Kalman filtering is used for estimating the event information to be transmitted. We can obtain the more accurate distance between the nodes by using the maximum likelihood estimation. Also we can derive the time value of uncertain events occurring in the wireless sensor network by using fuzzy predictor according to the distance between nodes and the amount of information to be transmitted. Then the wireless sensor nodes state transition can be controlled intelligently through combining its occurrence with the time value of deterministic event nodes and the input signal of the nodes. Simulation and experimental results show that energy-saving effect is very obvious by this state conversion strategy of energy saving for a large data quantity and data frequent acquisition.