Accurate available bandwidth allocation in http adaptive streaming

HTTP Adaptive Streaming (HAS) has been becoming a de facto standard for Over-the-top (OTT) video services. Typically, by adapting to network conditions, it provides smoother video quality perceived by the end users. However, when the network condition always fluctuates due to some reasons (e.g. bandwidth competition among HAS player or between HAS player and other applications), the perceived video quality might be deteriorated. This demands an effective approach to maintain specific Quality of Experience (QoE) level for the users. To do so, available bandwidth allocation is chosen as a common QoE control method. However, accurately allocating available bandwidth is still a challenge. In this paper, bandwidth allocation based on the relation between subjective Mean Opinions Score (MOS) and requested bitrate is proposed. The relation is captured by a regression model, which is applied to estimate the needed available bandwidth for the users. As the result of controlling the bandwidth, the users start to request the encoding bitrate equal to target bitrate after several requests, resulting in higher perceived video quality.