Adaptive prediction based approach for congestion estimation (APACE) in active queue management

摘要

Active Queue Management (AQM) policies provide an early indication of incipient congestion to the sources. In this paper, we propose a new AQM policy called APACE. APACE stands for Adaptive Prediction based Approach for Congestion Estimation in AQM that predicts the instantaneous queue length at a future time instant using adaptive filtering techniques. We compare the performance of APACE with other existing AQM schemes in networks having both single and multiple bottleneck links. We show that APACE is able to control the oscillations in the instantaneous queue. We also demonstrate, through exhaustive simulations, that APACE performs well in terms of link utilization even in networks with multiple bottleneck links. Moreover, APACE is not very sensitive to parameter settings and adapts quickly to changes in traffic.