基于指标相关性的网络运维质量评估模型

传统网络运维评估方法存在两方面的问题：一是在指标选取、权重指定等关键步骤过于依赖领域专家经验，难以得到精确全面的评估结果；二是通信设备用户数量不断增加带来了海量的数据，数据又来自多个厂家以及多种设备，传统方法处理此类海量异构数据的效率较低。为了解决这些问题，提出基于指标间互相关性的指标选取方法。该方法着眼于评估过程中指标选取步骤，通过比较指标数据序列间的相关性强弱，对原始指标集进行分类，在各个簇中选择代表性指标完成关键指标体系的构建；另外，结合无人工参与的数据处理方法、权重确定方法建立了网络运维质量评估模型。在实验中，所提方法选取的指标对人工指标的覆盖率为72.2%，并且比人工指标的信息重叠率少31%。所提方法能够有效减少人力参与，且评估结果对告警有较好的预测准确率。

Quality evaluation model of network operation and maintenance based on correlation analysis

Traditional network operation and maintenance evaluation method has two problems. First, it is too dependent on domain experts' experience in indicator selection and weight assignment, so that it is difficult to obtain accurate and comprehensive assessment results. Second, the network operation and maintenance quality involves data from multiple manufacturers or multiple devices in different formats and types, and a surge of users brings huge amounts of data. To solve the problems mentioned above, an indicator selection method based on correlation was proposed. The method focuses on the steps of indicator selection in the process of evaluation. By comparing the strength of the correlation between the data series of indicators, the original indicators could be classified into different clusters, and then the key indicators in each cluster could be selected to construct a key indicators system. The data processing methods and weight determination methods without human participation were also utilized into the network operation and maintenance quality evaluation model. In the experiments, the indicators selected by the proposed method cover 72.2% of the artificial indicators. The information overlap rate is 31% less than the manual indicators'. The proposed method can effectively reduce human involvement, and has a higher prediction accuracy for the alarm.