依赖大数据离群数据挖掘算法的业务系统间权限异构监控研究

Research on heterogeneous monitoring between business systems based on big data outlier mining algorithm

为提高业务系统间权限异构监控能力,本文提出了一种依赖大数据离群(Outliers of Large Data Sets,OLDS)数据挖掘算法的业务系统间权限异构监控方法(PermissiOns Heterogeneous Monitoring Between Business Systems,PHMBBS)。首先把业务系统间具有冲突性的各类业务分成不同的数据集合,并要求具有相近性质的大数据离群子集能够被分配在同一系统内,以此防止业务系统间权限异构监控中业务相互警报造成可调度性损失。监控系统根据业务监控评价结果,对无法分配到业务权限异构监控系统上的大数据离群进行拆分。实验结果表明,该系统异构监控能力高于同类系统,极大方便了整个医务系统的协调工作。

In order to improve the capability of permissions isomeric monitoring between business systems,a method of permissions heterogeneous monitoring between business systems is proposed based on Outliers of large data sets(OLDS)data mining algorithm(Permissions heterogeneous monitoring between business systems).Conflicting services are divided into different data sets,and large data outliers with similar properties can be assigned to the same system in order to prevent traffic alarm between business systems to cause schedulability loss.According to the results of business monitoring and evaluation,the monitoring system divides the outliers of big data on the heterogeneous monitoring system that can not be assigned to the business permissions.The experimental results show that the heterogeneous monitoring capability of the system is higher than that of the similar system,which greatly facilitates the coordination of the whole medical system.