Bufferbloat and Beyond : Removing Performance Barriers in Real-World Networks

Sammanfattning: The topic of this thesis is the performance of computer networks. While network performance has generally improved with time, over the last several years we have seen examples of performance barriers limiting network performance. In this work we explore such performance barriers and look for solutions.The problem of excess persistent queueing latency, known as bufferbloat, serves as our starting point; we examine its prevalence in the public internet, and evaluate solutions for better queue management, and explore how to improve on existing solutions to make them easier to deploy.Since an increasing number of clients access the internet through WiFi networks, examining WiFi performance is a natural next step. Here we also look at bufferbloat, as well as the so-called performance anomaly, where stations with poor signal strengths can severely impact the performance of the whole network. We present solutions for both of these issues, and additionally design a mechanism for assigning policies for distributing airtime between devices on a WiFi network. We also analyse the “TCP Small Queues” latency minimisation technique implemented in the Linux TCP stack and optimise its performance over WiFi networks.Finally, we explore how high-speed network processing can be enabled in software, by looking at the eXpress Data Path framework that has been gradually implemented in the Linux kernel as a way to enable high-performance programmable packet processing directly in the operating system’s networking stack.A special focus of this work has been to ensure that the results are carried forward to the implementation stage, which is achieved by releasing implementations as open source software. This includes parts that have been accepted into the Linux kernel, as well as a separate open source measurement tool, called Flent, which is used to perform most of the experiments presented in this thesis, and also used widely in the bufferbloat community.