Server and Content Selection for MPEG DASH Video Streaming with Client Information

Abstract

In HTTP adaptive streaming (HAS), such as MPEG DASH, the video is split into chunks and is available in different quality levels. If the video chunks are stored or cached on different servers to deal with the high load in the network and the Quality of Experience (QoE) requirements of the users, the problem of content selection arises. In this paper, we evaluate client-side algorithms for dynamically selecting an appropriate content server during DASH video streaming. We present three algorithms with which the DASH client itself can determine the most appropriate server based on client-specific metrics, like actual latency or bandwidth to the content servers. We evaluate and discuss the proposed algorithms with respect to the resulting DASH streaming behavior in terms of buffer levels and quality level selection.