Dynamic QoE-aware live streaming with clustering clients

In this paper, we propose a dynamic Quality of Experience (QoE)-aware live streaming algorithm by utilizing client clustering and similarity metrics. Encoding scheme of the proposed system finds a sufficient bitrate of the video and creates quality levels adapted to the distribution of clients’ bandwidth to improve overall average of user’s QoE. We show that the proposed system can improve structural similarity method (SSIM) performance when the client’s bandwidth is distributed in low or middle bandwidth, and decreases the number of clients who stop play back.