流的大小与传输速率相结合的双门限检测算法

提出基于流传输速率与数据量的双门限检测算法。为满足高速网络传输的性能要求，使用Hash表存储流检测的数据结构，将Hash表的冲突处理与基于流速率的缓存替换相结合以实现高效的大流检测,通过限制Hash桶的容量，确保报文的处理性能。真实网络数据的仿真测试结果表明：所提算法在相近的存储开销下，保持了较高的处理性能，准确性优于基于最近最少使用算法的大流检测及其派生算法以及基于统计计数的紧凑型空间节省算法。
A novel algorithm which is based on both the flows′ size and transmission rate was proposed for elephant flow detection. In order to meet the performance requirement of high speed networks, the data structure of elephant flow detection was indexed by Hash table, which combines the Hash conflict resolution with the eviction of cached flow entry to identify the elephant flow efficiently. A theoretical analysis was conducted to demonstrate the accuracy, performance and memory overhead of the detection algorithm. Experimental results on real data sets show that the proposed algorithm outperforms least recently used detection algorithm, its derivations and compact space saving detection algorithm in terms of accuracy and performance with similar memory overhead.