基于大數(shù)據(jù)的網(wǎng)絡隱患分析系統(tǒng)研究與應用

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摘要：文章提出了一種基于大數(shù)據(jù)技術的應用方式，通過挖掘告警強關聯(lián)規(guī)則深入挖掘網(wǎng)絡故障隱患，提升故障及隱患處理效率；通過構建季節(jié)性時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，對故障隱患進行有效預警，將故障隱患從被動處理的傳統(tǒng)模式革新到主動處理的預控層面上。

關鍵詞：大數(shù)據(jù)分析；告警關聯(lián)規(guī)則；故障預測

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)絡隱患主要通過人為方式對網(wǎng)絡告警及性能進行定性分析，無法有效挖掘出海量告警中的隱藏價值，不能實現(xiàn)多業(yè)務復雜網(wǎng)絡中的故障及隱患的快速處理[1]。（剩余3551字）