Network Characteristics of Video Streaming Traffic

TL;DR

This paper investigates the network traffic patterns of popular video streaming services, revealing diverse strategies influenced by application type and container, and models their impact on overall network traffic.

Contribution

It identifies different streaming strategies and develops an analytical model to assess their impact on Internet traffic, providing insights for network management.

Findings

Three distinct streaming strategies identified

Traffic patterns range from ON-OFF cycles to bulk transfer

Model predicts impact on aggregate network traffic

Abstract

Video streaming represents a large fraction of Internet traffic. Surprisingly, little is known about the network characteristics of this traffic. In this paper, we study the network characteristics of the two most popular video streaming services, Netflix and YouTube. We show that the streaming strategies vary with the type of the application (Web browser or native mobile application), and the type of container (Silverlight, Flash, or HTML5) used for video streaming. In particular, we identify three different streaming strategies that produce traffic patterns from non-ack clocked ON-OFF cycles to bulk TCP transfer. We then present an analytical model to study the potential impact of these streaming strategies on the aggregate traffic and make recommendations accordingly.