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基于改進(jìn)Kruskal算法的WSN故障節(jié)點(diǎn)檢測方法

發(fā)布時間:2018-03-31 06:00

  本文選題:無線傳感器網(wǎng)絡(luò) 切入點(diǎn):故障檢測 出處:《北京郵電大學(xué)學(xué)報》2014年04期


【摘要】:提出了一種基于改進(jìn)Kruskal算法的無線傳感器網(wǎng)絡(luò)(WSN)故障節(jié)點(diǎn)檢測方法.該方法首先通過集中式的改進(jìn)Kruskal最小生成樹算法來獲取可信的節(jié)點(diǎn)集合,之后依據(jù)可信節(jié)點(diǎn),采用鄰居節(jié)點(diǎn)比較算法對傳感器節(jié)點(diǎn)的感知值進(jìn)行分布式分析和處理,判定發(fā)生故障的傳感器節(jié)點(diǎn).同時為了容忍節(jié)點(diǎn)的臨時故障,引入了時間冗余.仿真結(jié)果表明,在節(jié)點(diǎn)故障率高達(dá)35%時,該方法依然能快速定位故障節(jié)點(diǎn),并且同時保證很高的檢測精確度.
[Abstract]:A novel fault node detection method for wireless sensor networks based on improved Kruskal algorithm is proposed in this paper. Firstly, a centralized improved Kruskal minimum spanning tree algorithm is used to obtain the trusted node set, and then, according to the trusted node, a new method is proposed. The neighbor node comparison algorithm is used to analyze and process the sensor node's perceptual value in a distributed way, and the sensor node is determined. In order to tolerate the temporary fault of the sensor node, time redundancy is introduced. The simulation results show that, When the failure rate of the node is as high as 35%, the method can still locate the fault node quickly and at the same time ensure the high detection accuracy.
【作者單位】: 北京郵電大學(xué)網(wǎng)絡(luò)與交換技術(shù)國家重點(diǎn)實(shí)驗(yàn)室;
【基金】:國家自然科學(xué)基金項目(61271187);國家自然科學(xué)基金創(chuàng)新研究群體科學(xué)基金項目(61121061) 國家高技術(shù)研究發(fā)展計劃項目(2013AA013502) 國家科技支撐計劃項目(2012BAH06B02)
【分類號】:TP212.9;TN929.5


本文編號:1689431

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