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校園網(wǎng)程控交換機連網(wǎng)故障斷點(diǎn)檢測技術(shù)研究
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武漢生物工程學(xué)院

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TP393

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Research on fault detection technology for campus network program-controlled switches
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    摘要:

    當前校園網(wǎng)程控交換機連網(wǎng)故障斷點(diǎn)檢測技術(shù)檢測準確率較低、誤警率高,也無(wú)法實(shí)現對故障斷點(diǎn)區域的精確定位,提出一種基于節點(diǎn)信譽(yù)感知模型的連網(wǎng)故障斷點(diǎn)檢測技術(shù)研究。依據校園網(wǎng)的網(wǎng)絡(luò )層次結構布局,構建節點(diǎn)之間的信譽(yù)感知模型,以提取節點(diǎn)故障區域特征信息,基于小波算法對感知信譽(yù)數據進(jìn)行預處理。為提高算法的穩定性,對鄰近節點(diǎn)之間的健康程度進(jìn)行分析,以最終實(shí)現對校園網(wǎng)程控交換機連網(wǎng)故障斷點(diǎn)的準確定位與檢測。仿真實(shí)驗數據表明,提出的斷點(diǎn)故障檢測技術(shù)在節點(diǎn)感知故障率為0.6的條件下,仍可獲得86.32%的檢測率。

    Abstract:

    At present, the detection technology of network fault breakpoint detection in the program control switch of the campus network is low, the false alarm rate is high, and the accurate location of the fault breakpoint area can not be realized, and a network fault breakpoint detection technology based on the node reputation perception model is proposed. According to the network hierarchy layout of the campus network, the credit perception model between nodes is built to extract the feature information of the node fault region, and the perceived reputation data is preprocessed based on the wavelet algorithm. In order to improve the stability of the algorithm, the health degree of the adjacent nodes is analyzed, so as to achieve the accurate location and detection of the breakpoints of the network program control switches in the campus network. The simulation data show that the proposed breakpoint fault detection technology still achieves 86.32% detection rate under the condition that the node sense failure rate is 0.6.

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施建.校園網(wǎng)程控交換機連網(wǎng)故障斷點(diǎn)檢測技術(shù)研究計算機測量與控制[J].,2019,27(1):56-59.

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歷史
  • 收稿日期:2018-07-03
  • 最后修改日期:2018-08-02
  • 錄用日期:2018-08-02
  • 在線(xiàn)發(fā)布日期: 2019-01-25
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