發(fā)布時(shí)間：2018-12-11 11:27

【摘要】：為提高不確定性無線傳感器網(wǎng)絡(luò)(wireless sensor network,WSN)模型的危險(xiǎn)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(luò)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(diǎn)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(duì)WSN網(wǎng)絡(luò)主節(jié)點(diǎn)、列表、輔助列表進(jìn)行更新,實(shí)現(xiàn)危險(xiǎn)連續(xù)局部前沿的實(shí)時(shí)更新,實(shí)現(xiàn)復(fù)雜危險(xiǎn)演變特征的分布式準(zhǔn)確預(yù)測(cè);最后,通過實(shí)驗(yàn)對(duì)比,所提方法對(duì)于傳感器節(jié)點(diǎn)故障和通信鏈路故障具有強(qiáng)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(shù)學(xué)院計(jì)算機(jī)信息系;淮北師范大學(xué)計(jì)算機(jī)學(xué)院;
【基金】：國家自然科學(xué)基金No.61102117 安徽高校自然科學(xué)研究重點(diǎn)項(xiàng)目No.KJ2016A782~~
【分類號(hào)】：TN929.5;TP212.9
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本文編號(hào)：2372463