Study of YouTube demand patterns in mixed public and campus WiFi network

In this paper we study traffic patterns in a large municipal WiFi network and in particular those of the most bandwidth hungry application, viz. YouTube, for which we provide a detailed analysis of demand in different geographical areas and over time. We consider the possibilities to reduce network traffic and increase Quality of Experience (QoE) by serving repeated requests for YouTube videos from caches placed either at the network head end, at the wireless access points, or in the user devices. Our data confirms that a significant part of the YouTube traffic can be served by such devices and that there exists a potential to optimize caching performance by exploiting the content demand locality. We also discover a previously unknown pattern of periodicity in content demand and present a simple example of how to exploit this in cache design.