Adaptive RED: An Algorithm for Increasing the Robustness of RED’s Active Queue Management

The RED active queue management algorithm allows network operators to simultaneously achieve high throughput and low average delay. However, the resulting average queue length is quite sensitive to the level of congestion and to the RED parameter settings, and is therefore not predictable in advance. Delay being a major component of the quality of service delivered to their customers, network operators would naturally like to have a rough a priori estimate of the average delays in their congested routers; to achieve such predictable average delays with RED would require constant tuning of the parameters to adjust to current traffic conditions. Our goal in this paper is to solve this problem with minimal changes to the overall RED algorithm. To do so, we revisit the Adaptive RED proposal of Feng et al. from 1997 [6, 7]. We make several algorithmic modifications to this proposal, while leaving the basic idea intact, and then evaluate its performance using simulation. We find that this revised version of Adaptive RED, which can be implemented as a simple extension within RED routers, removes the sensitivity to parameters that affect RED’s performance and can reliably achieve a specified target average queue length in a wide variety of traffic scenarios. Based on extensive simulations, we believe that Adaptive RED is sufficiently robust for deployment in routers.