Abstract
In recent years, video streaming traffic has increased exponentially over the Internet. This can be observed through the emergence of various video on demand sites such as Netflix, Amazon movies and others. In parallel, IEEE 802.11 (WiFi) technology has been deployed extensively from home to public areas. Although significant research has been done to address issues on video streaming through WiFi networks, it remains a challenging area. There are still interesting areas to be addressed especially to enhance user satisfaction in terms of Quality of Experience (QoE). After reviewing the existing research in improving video QoE through queuing in wireless environments, this paper propose a predictive packet drop technique to maintain a certain level of QoE based on predictive PSNR value without users' feedback. The proposed mechanism identifies packets as part of video frames and predicts the impact of their delay and loss on the resulting video performance. This reduces the need for client feedback and optimizes the resulting QoE of the delivered video. Therefore based on this information, the proposed algorithm can prioritize the video frames (I-, P- or B-Frames) whether to queue or drop in scenarios where bandwidth and limited. This method is evaluated using NS-3 simulator with Evalvid module.