Hypertext transfer protocol(HTTP) adaptive streaming(HAS) plays a key role in mobile video transmission. Considering the multi-segment and multi-rate features of HAS, this paper proposes a buffer-driven resource manag...Hypertext transfer protocol(HTTP) adaptive streaming(HAS) plays a key role in mobile video transmission. Considering the multi-segment and multi-rate features of HAS, this paper proposes a buffer-driven resource management(BDRM) method to enhance HAS quality of experience(QoE) in mobile network. Different from the traditional methods only focusing on base station side without considering the buffer, the proposed method takes both station and client sides into account and end user's buffer plays as the drive of whole schedule process. The proposed HAS QoE influencing factors are composed of initial delay, rebuffering and quality level. The BDRM method decomposes the HAS QoE maximization problem into client and base station sides separately to solve it in multicell and multi-user video playing scene in mobile network. In client side, the decision is made based on buffer probe and rate request algorithm by each user separately. It guarantees the less rebuffering events and decides which HAS segment rate to fetch. While, in the base station side, the schedule of wireless resource is made to maximize the quality level of all access clients and decides the final rate pulled from HAS server. The drive of buffer and twice rate request schemes make BDRMtake full advantage of HAS's multi-segment and multi-rate features. As to the simulation results, compared with proportional fair(PF), Max C/I and traditional HAS schedule(THS) methods, the proposed BDRM method decreases rebuffering percent to 1.96% from 11.1% with PF and from 7.01% with THS and increases the mean MOS of all users to 3.94 from 3.42 with PF method and from 2.15 with Max C/I method. It also guarantees a high fairness with 0.98 from the view of objective and subjective assessment metrics.展开更多
流媒体服务是流媒体技术在视频点播、在线直播、视频会议、远程教育等互联网信息服务中的应用总称,它带动了视频通信、视频消费和视频监控等业务的发展,并成为支撑智慧城市、智慧医疗、5G业务体系等工作的重要基础。目前的流媒体服务己...流媒体服务是流媒体技术在视频点播、在线直播、视频会议、远程教育等互联网信息服务中的应用总称,它带动了视频通信、视频消费和视频监控等业务的发展,并成为支撑智慧城市、智慧医疗、5G业务体系等工作的重要基础。目前的流媒体服务己脱离纯技术驱动的模式,正在走向技术与服务相结合、体验与互动并进的新模式,有效地改善了用户体验质量(Quality of Experience,QoE),是明确把握用户需求、优化服务、提高市场竞争力的关键。然而现实中网络环境的复杂不稳定导致流媒体服务经常会出现质量波动(码率变化)、卡顿的发生,这些都会导致用户的感知QoE的下降,从而降低对流媒体服务的满意度。因此,提供满意的QoE成为各大运营商、内容供应商的目标。通过流媒体码率调节来进行QoE的优化,取得以下进展:采取的码率调节策略是将视频播放分为初始启动阶段和稳定播放阶段,并且为每个阶段采取不同的优化目标,前者旨在缩短启动延迟,后者则改善视频质量和降低重载的次数。该策略与使用经典的码率适应方法相比较,可以有效减少由于请求播放的视频码率与波动网络吞吐量之间的不匹配而导致重载的发生,并且在实时QoE的提升上获得了出色的性能。展开更多
受网络吞吐量及稳定性等因素影响,无线网络中的移动视频业务体验欠佳。为了提升移动视频用户体验质量(QoE,Quality of Experience),本文提出一种自由视频码率选择算法,不再对所有用户使用统一的低等级初始码率,而根据用户不同的网络状...受网络吞吐量及稳定性等因素影响,无线网络中的移动视频业务体验欠佳。为了提升移动视频用户体验质量(QoE,Quality of Experience),本文提出一种自由视频码率选择算法,不再对所有用户使用统一的低等级初始码率,而根据用户不同的网络状态来确定码率自适应传输的初始视频码率;同时,在视频播放过程中控制码率平稳变化。仿真实验利用Matlab软件,采用"停等"策略模拟LTE网络中的实时视频传输,以QoE评分为性能度量,验证本文方法的有效性。展开更多
基金supported by the 863 project (Grant No. 2014AA01A701) Beijing Natural Science Foundation (Grant No. 4152047)
文摘Hypertext transfer protocol(HTTP) adaptive streaming(HAS) plays a key role in mobile video transmission. Considering the multi-segment and multi-rate features of HAS, this paper proposes a buffer-driven resource management(BDRM) method to enhance HAS quality of experience(QoE) in mobile network. Different from the traditional methods only focusing on base station side without considering the buffer, the proposed method takes both station and client sides into account and end user's buffer plays as the drive of whole schedule process. The proposed HAS QoE influencing factors are composed of initial delay, rebuffering and quality level. The BDRM method decomposes the HAS QoE maximization problem into client and base station sides separately to solve it in multicell and multi-user video playing scene in mobile network. In client side, the decision is made based on buffer probe and rate request algorithm by each user separately. It guarantees the less rebuffering events and decides which HAS segment rate to fetch. While, in the base station side, the schedule of wireless resource is made to maximize the quality level of all access clients and decides the final rate pulled from HAS server. The drive of buffer and twice rate request schemes make BDRMtake full advantage of HAS's multi-segment and multi-rate features. As to the simulation results, compared with proportional fair(PF), Max C/I and traditional HAS schedule(THS) methods, the proposed BDRM method decreases rebuffering percent to 1.96% from 11.1% with PF and from 7.01% with THS and increases the mean MOS of all users to 3.94 from 3.42 with PF method and from 2.15 with Max C/I method. It also guarantees a high fairness with 0.98 from the view of objective and subjective assessment metrics.
文摘流媒体服务是流媒体技术在视频点播、在线直播、视频会议、远程教育等互联网信息服务中的应用总称,它带动了视频通信、视频消费和视频监控等业务的发展,并成为支撑智慧城市、智慧医疗、5G业务体系等工作的重要基础。目前的流媒体服务己脱离纯技术驱动的模式,正在走向技术与服务相结合、体验与互动并进的新模式,有效地改善了用户体验质量(Quality of Experience,QoE),是明确把握用户需求、优化服务、提高市场竞争力的关键。然而现实中网络环境的复杂不稳定导致流媒体服务经常会出现质量波动(码率变化)、卡顿的发生,这些都会导致用户的感知QoE的下降,从而降低对流媒体服务的满意度。因此,提供满意的QoE成为各大运营商、内容供应商的目标。通过流媒体码率调节来进行QoE的优化,取得以下进展:采取的码率调节策略是将视频播放分为初始启动阶段和稳定播放阶段,并且为每个阶段采取不同的优化目标,前者旨在缩短启动延迟,后者则改善视频质量和降低重载的次数。该策略与使用经典的码率适应方法相比较,可以有效减少由于请求播放的视频码率与波动网络吞吐量之间的不匹配而导致重载的发生,并且在实时QoE的提升上获得了出色的性能。
文摘受网络吞吐量及稳定性等因素影响,无线网络中的移动视频业务体验欠佳。为了提升移动视频用户体验质量(QoE,Quality of Experience),本文提出一种自由视频码率选择算法,不再对所有用户使用统一的低等级初始码率,而根据用户不同的网络状态来确定码率自适应传输的初始视频码率;同时,在视频播放过程中控制码率平稳变化。仿真实验利用Matlab软件,采用"停等"策略模拟LTE网络中的实时视频传输,以QoE评分为性能度量,验证本文方法的有效性。
