Improving PIE's performance over high-delay paths

TL;DR

This paper introduces MADPIE, an extension to PIE that adds deterministic drops to better control queuing delay in high-RTT networks, improving performance for latency-sensitive traffic without harming bulk transfer efficiency.

Contribution

MADPIE extends PIE with deterministic packet drops to effectively manage high-delay paths, reducing queuing delays and enhancing performance for VoIP and small downloads.

Findings

MADPIE reduces maximum queuing delays at high RTTs.

MADPIE improves VoIP and small file download performance.

MADPIE does not negatively impact bulk transfer throughput.

Abstract

Bufferbloat is excessive latency due to over- provisioned network buffers. PIE and CoDel are two recently proposed Active Queue Management (AQM) algorithms, designed to tackle bufferbloat by lowering the queuing delay without degrading the bottleneck utilization. PIE uses a proportional integral controller to maintain the average queuing delay at a desired level; however, large Round Trip Times (RTT) result in large spikes in queuing delays, which induce high dropping probability and low utilization. To deal with this problem, we propose Maximum and Average queuing Delay with PIE (MADPIE). Loosely based on the drop policy used by CoDel to keep queuing delay bounded, MADPIE is a simple extension to PIE that adds deterministic packet drops at controlled intervals. By means of simulations, we observe that our proposed change does not affect PIE's performance when RTT < 100 ms. The deterministic drops are more dominant when the RTT increases, which results in lower maximum queuing delays and better performance for VoIP traffic and small file downloads, with no major impact on bulk transfers.