现代电子技术
現代電子技術
현대전자기술
MODERN ELECTRONICS TECHNIQUE
2014年
16期
45-48
,共4页
罚因子%体验度%自适应带宽估计%DASH
罰因子%體驗度%自適應帶寬估計%DASH
벌인자%체험도%자괄응대관고계%DASH
penalty factor%quality of experience%adaptive bandwidth estimation%DASH
随着移动互联网的普及,基于DASH的流媒体传输协议的应用越来越广泛。如何在带宽波动较大的移动互联网环境中保证用户实现流媒体的流畅点播,提高用户的体验度是DASH调度算法最主要研究的问题。以提高用户体验度为出发点,结合带宽和缓存深度两方面因素,对带宽预测模型的置信度进行评价。在高置信度情况下,大胆地对网络带宽估计模型的模型参量进行调整;在低置信度情况下,以保护缓冲区深度为目的,谨慎地对模型参量进行调整。这种调整势必会对QoE造成相应的影响,该影响作为“罚因子”反馈回模型置信度的评价,以获得模型参数的动态最优解,得到一种较好的DASH调度算法。
隨著移動互聯網的普及,基于DASH的流媒體傳輸協議的應用越來越廣汎。如何在帶寬波動較大的移動互聯網環境中保證用戶實現流媒體的流暢點播,提高用戶的體驗度是DASH調度算法最主要研究的問題。以提高用戶體驗度為齣髮點,結閤帶寬和緩存深度兩方麵因素,對帶寬預測模型的置信度進行評價。在高置信度情況下,大膽地對網絡帶寬估計模型的模型參量進行調整;在低置信度情況下,以保護緩遲區深度為目的,謹慎地對模型參量進行調整。這種調整勢必會對QoE造成相應的影響,該影響作為“罰因子”反饋迴模型置信度的評價,以穫得模型參數的動態最優解,得到一種較好的DASH調度算法。
수착이동호련망적보급,기우DASH적류매체전수협의적응용월래월엄범。여하재대관파동교대적이동호련망배경중보증용호실현류매체적류창점파,제고용호적체험도시DASH조도산법최주요연구적문제。이제고용호체험도위출발점,결합대관화완존심도량방면인소,대대관예측모형적치신도진행평개。재고치신도정황하,대담지대망락대관고계모형적모형삼량진행조정;재저치신도정황하,이보호완충구심도위목적,근신지대모형삼량진행조정。저충조정세필회대QoE조성상응적영향,해영향작위“벌인자”반궤회모형치신도적평개,이획득모형삼수적동태최우해,득도일충교호적DASH조도산법。
As the mobile network has become universal in recent years,DASH-based streaming media transmission proto-col is used more and more widely. Thus,how to guarantee the fluent video-on-demand in the mobile network circumstance with large bandwidth fluctuation and improve the quality of experience(QoE)are the major problems for DASH algorithm. In this pa-per,in order to improve the users’QoE,an evaluation on the confidence coefficient of the bandwidth prediction model is adopted in combination with the bandwidth and buffer depth. A bold adjustment of network bandwidth estimation model parame-ters under the condition of high degree of confidence. A careful adjustment of the model parameters should be conducted to pro-tect the buffer depth under the condition of low degree of confidence. This adjustment will certainly cause corresponding influence on the QoE. The influence will be taken as the "penalty factor" evaluation of feedback back to the model confidence level for dy-namic optimal solution of model parameters and better DASH scheduling algorithm.