An Optimization-based Resource Management Strategy to Maximize QoE for Real-time Video Streaming Services

碩士 === 國立臺灣大學 === 資訊管理學研究所 === 107 === The technology of video transmission with television and movies wide boom so that promote quickly development .In early time, users only in fixed time, fixed location, already perfected full media data can enjoy fluently movies. Recent year, with the progress o...

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Bibliographic Details
Main Authors: Yi-Bing Luo, 羅一冰
Other Authors: Yeong-Sung Lin
Format: Others
Language:en_US
Published: 2019
Online Access:http://ndltd.ncl.edu.tw/handle/e4cu8g
Description
Summary:碩士 === 國立臺灣大學 === 資訊管理學研究所 === 107 === The technology of video transmission with television and movies wide boom so that promote quickly development .In early time, users only in fixed time, fixed location, already perfected full media data can enjoy fluently movies. Recent year, with the progress of science and technology, the fast development of internet and the pace of life gradually accelerate, more and more users need to high quality of service in video, lead to the technology of video transmission was more and more attention to QoE . The technology of video transmission from static picture or only sound deliver to both sound and picture synchronization. During the user enjoy video time; video streaming maybe happens broke off or fluently. It is huge impact to QoE. It including waiting time,video streaming fluently and so on. Traditionally methods is only set the buffer size for user, or only Prefetching user’s favorite video. In this research, we proposal a new resource management that combination set the buffer size and Prefetching users favorite video to maximize QoE. The paper the perspective of media player, to set dynamic buffer size for user and buffer size for Prefetching favorite video, at the same time we focus on control of overflow video streaming and control of under of underflow video streaming. It is improve QoE. We propose an optimization-based resource management strategy to maximize QoE for real-time video streaming services.