一种参数自适应的主动队列管理算法—自适应BLUE

An Adaptive Active Queue Management Algorithm—Self-Adaptive BLUE

BLUE算法是一种典型的主动队列管理(Active Queue Management,AQM)算法,研究表明BLUE算法优于RED算法。BLUE算法使用丢包事件和链路空闲事件控制网络拥塞。但由于BLUE算法在参数设置方面存在不足,尤其是当TCP连接数突然剧烈变动时,容易导致队列溢出或空闲的频繁发生。该文引进参数自适应机制,提出了自适应BLUE算法,并借鉴了RED算法的早期拥塞检测机制。NS仿真实验表明该算法能有效保持队列长度的稳定,减少队列溢出或空闲现象的发生,在提高链路利用率的同时降低丢包率。

As a classical Active Queue Management （AQM） algorithm, compared with RED （Random Early Detection）, BLUE has many advantages. BLUE uses packet loss and link idle events to maanage congestion. However, there are still some insufficiencies in parameter setting for BLUE. Especially when TCP connections changed dramatically will lead to queue overflow and underflow. Based on the study of BLUE, a novel self-adaptive BLUE is proposed. NS simulation results show that the algorithm can effectively stabilize the queue occupation independent of the number of active TCP connections and mitigate the queue overflow and underflow, it can improve link utilization and decrease packet loss rate at the same time.