依据流统计特性的报文分类规则集动态优化

Dynamic optimization of packet classification rules organization based on Internet traffic statistical characters

针对普遍使用的线性搜索报文分类方法在时间效率方面的固有弱点,设计了一种依据数据流统计特性的规则集自适应动态优化算法。其中包括:规则权重计算、规则优化排序、动态触发优化等部分。在占用较少资源的情况下,较为有效地提高了系统性能,并经实验结果证明,应用效果良好。

Aimed at the natural weakness of the commonly used linear search packet classification algorithm in the aspect of time efficiency,this paper proposed a novel algorithm which dynamically optimized the rules organization based on the Internet traffic statistical characteristics.This algorithm included calculating the weights of rules,optimizing the order of rules,dynamically triggered optimizing and so on.Because of the minimized resource consumption,this algorithm can practically improve the system performance and is shown to be efficient in the actual tests.