發(fā)布時間：2018-12-11 11:27

【摘要】：為提高不確定性無線傳感器網(wǎng)絡(wireless sensor network,WSN)模型的危險邊界局部演化特性感知精度,提出了一種基于局部聚類的不確定性WSN模型網(wǎng)絡局部前沿協(xié)同更新算法。首先,給出基于高斯的WSN感知距離不確定性模型和速度不確定性模型,并給出封閉形式的考慮WSN節(jié)點有限處理能力和能量約束的連續(xù)貝葉斯局部前沿速度更新模型;其次,基于局部聚類更新算法對WSN網(wǎng)絡主節(jié)點、列表、輔助列表進行更新,實現(xiàn)危險連續(xù)局部前沿的實時更新,實現(xiàn)復雜危險演變特征的分布式準確預測;最后,通過實驗對比,所提方法對于傳感器節(jié)點故障和通信鏈路故障具有強大的魯棒性。
[Abstract]:In order to improve the perceptual accuracy of the local evolution characteristics of uncertain (wireless sensor network,WSN (Wireless Sensor Network) model, a local frontier collaborative updating algorithm based on local clustering for uncertain WSN model is proposed. Firstly, the WSN perceptual distance uncertainty model and velocity uncertainty model based on Gao Si are given, and the continuous Bayesian local frontier velocity updating model considering the limited processing capacity and energy constraints of WSN nodes is given. Secondly, the main node, list and auxiliary list of WSN network are updated based on the local clustering updating algorithm to realize the real-time updating of the continuous local frontier of danger and the accurate and distributed prediction of the complex risk evolution characteristics. Finally, the proposed method is robust to sensor node fault and communication link fault through experimental comparison.
【作者單位】： 宿州職業(yè)技術學院計算機信息系;淮北師范大學計算機學院;
【基金】：國家自然科學基金No.61102117 安徽高校自然科學研究重點項目No.KJ2016A782~~
【分類號】：TN929.5;TP212.9
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本文編號：2372463