A scheduling scheme for stochastic event capture based on Bayes statistical method

The off-line scheduling scheme of existing wireless sensor network is improved in this paper. Firstly, Bayesian method is introduced and Poisson distribution parameter followed by the number of sensor nodes is regarded as a random variable. We estimate the parameter by Bayesian posteriori estimate and obtain Bayesian estimated correction value. Then, we discuss the relationship between instantaneous event capture probability, average capture probability, average capture energy efficiency and Bayesian estimate value of the distribution parameter. Finally, considering the fact that Bayesian estimation value can be adjusted automatically after posterior samples are included, we propose an online scheduling scheme for asynchronous wireless sensor network. Through simulation comparison between online scheduling scheme and off-line scheduling scheme, our results show that online scheduling scheme can lower the probability of failure to capture stochastic events, increase the probability of capturing events and further save the energy of wireless sensor network, and be more flexible to capturing stochastic events. Moreover, expanding the perception radius of sensors can also enhance capture efficiency on the basis of controlling the working duration of wireless sensor network.