TAILIEUCHUNG - QoE optimization based on quality delay trade off model for adaptive streaming with multiple VBR videos
In this paper, we propose a quality optimization solution for variable bitrate (VBR) video streaming which allows components inside the network to select an appropriate version for each HAS client. The experiments in real-time conditions show that our method can provide each HAS client with the best possible quality while meeting the constraints of overall bandwidth and delay. | Journal of Science & Technology 131 (2018) 055-061 QoE Optimization Based on Quality-delay Trade-off Model for Adaptive Streaming with Multiple VBR Videos Nguyen Thi Kim Thoa*, Pham Hong Thinh, Pham Ngoc Nam Hanoi University of Science and Technology – No. 1, Dai Co Viet Str., Hai Ba Trung, Ha Noi, Viet Nam Received: November 22, 2018; Accepted: November 26, 2018 Abstract HTTP adaptive streaming (HAS) as a part of multi-bitrate streaming, has attracted significant attention over the past few years. Although offering many advantages such as easy deployment and effective cost, HAS faces some challenges in providing users with high video quality. In managed networks (., IPTV), the purely client-driven approaches of current HAS cause competing behavior, excessive quality oscillations, which negatively affect user experience. Some recent studies have proposed network-based solutions to overcome these problems; however, they just target at constant bitrate (CBR) videos. In this paper, we propose a quality optimization solution for variable bitrate (VBR) video streaming which allows components inside the network to select an appropriate version for each HAS client. The experiments in real-time conditions show that our method can provide each HAS client with the best possible quality while meeting the constraints of overall bandwidth and delay. Keywords: Adaptive Streaming, QoE, Optimization, Variable bitrate (VBR). 1. Introduction* Nonetheless, the existing methods are limited to CBR videos. Recently, multi-bitrate adaptive streaming such as HTTP adaptive streaming (HAS) has become a new trend in multimedia networks [1]. For adapting to network and terminal capabilities, a streaming provider should generate multiple alternatives (or versions) of an original video in advance. Given the current bandwidth, a specific version will be selected for high video quality. HAS can be deployed for constant bitrate (CBR) video or variable bitrate (VBR) video. Basically, VBR .
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