关键词: 不确定性模型, 无线传感器网络, 连续前沿, 局部聚类, 协同更新

Abstract: In order to improve the sensing accuracy of the local evolution of the risk boundary of uncertain wireless sensor network (WSN) model, this paper conducts a Gauss collaborative local clustering updating of continuous frontier for uncertainty WSN. Firstly, this paper presents the distance uncertainty model and velocity uncertainty model, and also gives the closed form of the continuous Bayesian local front velocity update model, which considers the limited processing power of WSN node and energy constraints. Secondly, the local clustering update algorithm is used to update the master node, the list and the auxiliary list for WSN, which realizes the real-time update of the continuous local front of the danger, and also realizes the distributed accurate prediction of the complicated risk evolution. Finally, the experimental results show that the proposed method is robust to sensor node failures and communication link failures.

Key words: uncertainty model, wireless sensor network, continuous front, local clustering, cooperative update