Scheduling strategy for Hidden Markov Model in wireless sensor network

In this paper, a novel sensor scheduling scheme based on Hidden Markov Model (HMM) is proposed for wireless sensor network (WSN). The main idea of this paper is to devise an optimal scheduling algorithm to select sensor nodes to provide the next measurement for the next time. Sensor scheduling process is formulated as a double stochastic process to obtain the reasonable state path. In the process of calculation, we use the forward probability and backward probability to decrease the computation complexity. The simulation results show that this method can effectively reduce energy consumption and extend the lifetime of the sensor network. It has great value in practical application.