摘要: 针对最近最久未使用(LRU)算法在高速网络中大流漏判率高的缺陷,提出一种基于多粒度最近最久未使用检测算法。该算法采用分层多粒度压缩计数机制对高速网络数据抽样,提高对长流的识别精度。基于实际的互联网数据进行仿真实验,结果表明,在给定条件下,该方法的内存占用量为LRU算法的50%,测量误差仅为LRU算法的10%。
关键词:
流量测量,
多粒度压缩计数,
最近最久未使用
Abstract: Aiming at the lack of the high false negative ratio of Least Recently Used(LRU) algorithm in high-speed network traffic measurement, this paper proposes a new algorithm which is based on the Multi-Granularity Least Recently Used(MGLRU). The algorithm employs hierarchical multi-granularity compression counting mechanism for high-speed network data sampling, and improves the accuracy of the long-term flow detection. And based on the real Internet data, simulation results show that: in the given conditions, the algorithm uses about 50 percent of the memory consumption and has 10 percent of relative error compared with the LRU algorithm.
Key words:
traffic measurement,
multi-granularity compressed counting,
Least Recently Used(LRU)
中图分类号:
张果, 陈庶樵, 张震, 陈红梅. 基于MGLRU的IP流统计算法[J]. 计算机工程, 2010, 36(17): 141-143,146.
ZHANG Guan, CHEN Shu-Qiao, ZHANG Shen, CHEN Gong-Mei. IP Flow Statistics Algorithm Based on MGLRU[J]. Computer Engineering, 2010, 36(17): 141-143,146.