Abstract
The wireless sensor network (WSN) has great prospects in monitoring and control of industrial plants and devices. One of the main challenges of developing WSNs for industrial applications is to satisfy their requirements for reliability with strict bounds. Accurate prediction of a radio link's reliability is helpful for upper layer protocols to optimise network level quality of service (QoS) performance. In this paper, to predict the bounds of the confidence interval of the packet reception ratio (PRR), a radio link reliability prediction (RLRP) model is proposed for describing the relation between the reliability metric's bounds and factors that affect it. Based on the RLRP model, the adaptive extended Kalman filter algorithm is adopted to predict the reliability metric. Real-world experiments were performed to demonstrate the proposed model. The results indicate that our RLRP model is accurate in predicting the bounds of link reliability, can better reflect the random characteristic of the radio link, and is more sensitive to dynamic changes of the radio link.
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