Network-Dependent Server Performance Analysis of HTTP Adaptive Streaming

Abstract

The HTTP adaptive streaming (HAS) is a popular mechanism for delivery of live and on-demand video contents encoded with different qualities and divided into segments with equal length. The mechanism adapts the requested segment qualities to the quality of the link, providing uninterrupted service even in congested network conditions. In this work, we analyze the HAS for delivery of Video on Demand (VoD) contents from server performance point of view for different segment lengths and different network conditions. For that purpose, we created an environment for real-case measurements of the server performance and measured performance parameters like CPU utilization, generated in-bound and out-bound traffic and number of established TCP connections. From the analysis of the obtained data, we conclude that streaming of shorter video segments generates more appropriate and predictable traffic pattern, but requires more CPU power and TCP connections. Therefore, the shorter contents are suitable for streaming in networks with very low packet losses. Longer video segments, on the other hand, tend to require more resources only at the beginning of the streaming session, which they release before the end of the session, and hence, alleviate the network equipment. The main advantage of using long segments is that they can achieve uninterrupted streaming experience even in harsh network environments such as congested wireless networks.