基于统计分析的许可回收规则定义与应用

Statistics-based rule definition and application for license recycling

针对许可回收规则中特征项和阈值的选取缺少定量分析的模型和方法的问题,本文在形式化定义参数模型的基础上,综合使用差分编码、信息熵和相关矩阵等统计分析方法描述特征敏感性和相关性,并提出了敏感突出、代价最小化、趋零一致性和翻倍稳定原则,以筛选特征项、界定阈值。根据用户使用企业级软件的数据,该方法能够从多个候选项中,选定CPU利用率作为许可回收规则唯一的特征项,并设定阈值为8%,判定时间间隔为1 136 s。实验结果表明,该方法简单有效,而且易于编程实现。

Existing feather and threshold selection lack quantitative models and methods in license recycling rule. We analyze feature sensitivity and correlation by such statistical methods as differential coding, information entropy, correlation matrix, based on formalization defined parameter model. We also define feathers and threshold with sensitivity, cost minimization, convergence consistency and stability principles. The method can select CPU utilization rate as the only feature item from several candidates and set the threshold of 8% and status-check interval of 1136 s. Experimental results show that it Js simple, effective and easily programed.