基于大數(shù)據(jù)的網(wǎng)絡(luò)隱患分析系統(tǒng)研究與應(yīng)用

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摘要：文章提出了一種基于大數(shù)據(jù)技術(shù)的應(yīng)用方式，通過(guò)挖掘告警強(qiáng)關(guān)聯(lián)規(guī)則深入挖掘網(wǎng)絡(luò)故障隱患，提升故障及隱患處理效率；通過(guò)構(gòu)建季節(jié)性時(shí)間序列分析模型揭示歷史數(shù)據(jù)中故障隱患發(fā)生、發(fā)展的規(guī)律，對(duì)故障隱患進(jìn)行有效預(yù)警，將故障隱患從被動(dòng)處理的傳統(tǒng)模式革新到主動(dòng)處理的預(yù)控層面上。

關(guān)鍵詞：大數(shù)據(jù)分析；告警關(guān)聯(lián)規(guī)則；故障預(yù)測(cè)

Research and Application of Network Hazard Analysis System Based on Big Data

ZHANG Rui， HUANG Jianbo， WANG Ruyue， ZHU Kunyuan， ZHAN Pengfei

（China Mobile Communications Corporation， Guangzhou 510000， China）

Abstract： The article proposes an application method based on big data technology， which deeply mines network fault hidden dangers by mining strong alarm association rules， and improves the efficiency of fault and hidden danger processing; By constructing a seasonal time series analysis model to reveal the occurrence and development patterns of fault hazards in historical data， effective early warning of faults and hazards can be provided， and fault hazards can be innovated from the traditional passive processing mode to the proactive pre control level.

Key words： big data analysis; alarm association rules; fault prediction

現(xiàn)階段網(wǎng)絡(luò)隱患主要通過(guò)人為方式對(duì)網(wǎng)絡(luò)告警及性能進(jìn)行定性分析，無(wú)法有效挖掘出海量告警中的隱藏價(jià)值，不能實(shí)現(xiàn)多業(yè)務(wù)復(fù)雜網(wǎng)絡(luò)中的故障及隱患的快速處理[1]。（剩余3551字）