IBLUE:一种新的主动队列管理算法
IBLUE:A Novel Active Queue Management Method
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摘要: 针对日益严重的网络拥塞现象,在传统的BL U E算法的基础上建立了一种新的主动队列管理方法(Im-mune clonal simulated annealing-based BLUE,IBLUE)。该方法重新定义队列长度变化范围以及丢包概率,并且利用免疫克隆模拟退火算法来刻画队列长度变化情况。其次,以实际数据进行仿真实验,深入分析了影响该方法的关键因素,同时通过对比BLUE和BLUE+算法性能,结果表明IBLUE具有较好的适应性。Abstract: In order to mitigate the network congestion problem,a novel active queue management method (Immune clonal simulated annealing-based BLUE,IBLUE) is proposed by BLUE algorithm.In this method,the range of queue length and dropping rate are re-defined,and the average queue length is depicted by immune clonal simulated annealing.Then,a simulation with actual data was conducted to study key factor in IBLUE.The results show that, compared to BLUE and BLUE+,IBLUE has better adaptability.
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