Abstract
We improve the off-line scheduling scheme of existing wireless sensor network. Firstly, we introduce Bayesian statistical method in synchronous wireless sensor network. Then, we let duration and interval, the reflection of characteristics of stochastic events, obey exponential distribution. Next, we make Bayes posterior estimation on parameter. Based on Bayesian estimate, we obtain the analytical solution of the capture probability of stochastic events and sensor energy efficiency of capture events. Finally, we propose an on-line scheduling scheme for synchronous wireless sensor networks. This paper compares and analyzes the simulation experiments in on-line scheduling scheme and off-line scheduling scheme, and the results show that compared with off-line scheduling scheme with constant distribution parameter values, on-line scheduling scheme can effectively reduce the probability of missing stochastic events and increase the probability of capturing events, further save energy consumption of wireless sensor network, and extend network lifetime.
Highlights
The Internet of Things (IoT), the currently most popular research area, refers to realtime monitoring and connecting objects through various sensor devices and technologies to collect event information, and having the access to the network, it realizes the ubiquitous connection between object and object as well as object and people
How to schedule the active and inactive state of the sensor in Wireless sensor networks (WSN) saves the energy of sensor network as much as possible, and extending sensor network lifetime is a hot issue in current research
5 On-line adjustable periodic schedule Based on above analysis, we study on-line scheduling scheme in synchronous WSN
Summary
The Internet of Things (IoT), the currently most popular research area, refers to realtime monitoring and connecting objects through various sensor devices and technologies to collect event information, and having the access to the network, it realizes the ubiquitous connection between object and object as well as object and people. Based on the research made by He et al [15], we study on-line scheduling issue of sensors in synchronous WSN and propose a real-time adjustable sensor inactive period scheduling scheme to make it more in line with randomness of stochastic event, more adaptable, and further save energy consumption of network. The authors assumed that the interval of event columns is independently and identically distributed random variables and these random variables obey exponential distribution with determined parameters, and studied the inactive state scheduling issue of sensor coverage subset. 3.1 Prior distribution of stochastic events Unlike off-line scheduling scheme, this paper first gives Bayesian estimation of duration and interval distribution parameter describing the randomness of event. Bayes posterior estimated value of exponential distribution parameter θ−1 obeyed by stochastic event duration variable X is 1=θBnayes. Bayes posterior estimated value of exponential distribution parameter β−1 obeyed by stochastic event duration variable Y is 1=βBnayes
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