{'fraction_non_alphanumeric': 0.02540220152413209, 'fraction_numerical': 0.0, 'mean_word_length': 5.0, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Study of user QoE improvement for dynamic adaptive streaming over HTTP (MPEG-DASH)

Video streaming over HTTP is becoming the de facto dominating paradigm for today's video applications. HTTP as an over-the-top (OTT) protocol has been leveraged for quality video traversal over the Internet. High user-received quality-of-experience (QoE) is driven not only by the new technology, but also by a wide range of user demands. Given the limitation of a traditional TCP/IP network for supporting video transmission, the typical on-off transfer pattern is inevitable. Dynamic adaptive streaming over HTTP (DASH) establishes a simple architecture and enables new video applications to fully utilize the exiting physical network infrastructure. By deploying robust adaptive algorithms at the client side, DASH can provide a smooth streaming experience. We propose a dynamic adaptive algorithm in order to keep a high QoE for the average user's experience. We formulated our QoE optimization in a set of key factors. The results obtained by our empirical network traces show that our approach not only achieves a high average QoE but it also works stably under different network conditions.