Forecasting Full-Path Network Congestion Using One Bit Signalling

TL;DR

This paper introduces a novel 1-bit signalling scheme called Probabilistic Congestion Notification (PCN) that enables sources to accurately estimate and predict network congestion levels along the path, improving congestion management.

Contribution

The paper presents a new congestion estimation method using 1-bit ECN and time series analysis, allowing for precise, predictive congestion awareness in network sources.

Findings

Successfully estimates congestion with low error in simulations

Enables proactive congestion avoidance by sources

Uses real Internet traffic traces for validation

Abstract

In this paper, we propose a mechanism for packet marking called Probabilistic Congestion Notification (PCN). This scheme makes use of the 1-bit Explicit Congestion Notification (ECN) field in the Internet Protocol (IP) header. It allows the source to estimate the exact level of congestion at each intermediate queue. By knowing this, the source could take avoiding action either by adapting its sending rate or by using alternate routes. The estimation mechanism makes use of time series analysis both to improve the quality of the congestion estimation and to predict, ahead of time, the congestion level which subsequent packets will encounter. The proposed protocol is tested in ns-2 simulator using a background of real Internet traffic traces. Results show that the methods can successfully calculate the congestion at any queue along the path with low error levels.