Rapid Signalling of Queue Dynamics

TL;DR

This paper introduces a new metric called 'scaled sojourn time' to reduce the delay in congestion signals within queue management, aiming to improve load regulation and reduce delay peaks.

Contribution

It proposes 'scaled sojourn time' as a novel metric that scales queuing delay to better reflect queue dynamics and removes randomness-induced delays in signals.

Findings

Scaled sojourn time effectively reduces congestion signal delay.

The method improves queue regulation and reduces delay peaks.

Removing randomness delays enhances signal accuracy.

Abstract

Rather than directly considering the queuing delay of data, this memo focuses on reducing the delay that congestion signals experience within a queue management algorithm, which can be greater than the delay that the data itself experiences within the queue. Once the congestion signals are delayed, regulation of the load becomes more sloppy, and the queue tends to overshoot and undershoot more as a result, leading the data itself to experience greater peaks in queuing delay as well as intermittent under-utilization. Where the service rate of a queue varies, it is preferable to measure the queue in units of time not bytes. However, the size of the queued backlog can be measured in bytes and signalled at the last instant as data leaves the queue, whereas measuring queuing delay introduces inherent delay. This paper proposes 'scaled sojourn time', which scales queuing delay by the ratio between the backlogs at dequeue and enqueue. This is equivalent to scaling the sojourn time by the ratio of the arrival and departure rates averaged over the time spent in the queue. The paper also proposes the removal of delays due to randomness in the signal encoding.