A DASH Client Optimization Algorithm Based on Multiple Servers

doi:10.19678/j.issn.1000-3428.0048773

Abstract

Abstract: In the transmission of Dynamic Adaptive Streaming over HTTP(DASH) for scenario,the client’s video quality would fluctuate much frequently due to the user’s high dynamic request and different transmission bandwidths of multiple servers.Such fluctuation would affect the Quality of Experience(QoE) seriously.To solve this problem,this paper proposes a video fragment request scheduling algorithm based on Software-Defined Network(SDN).By considering several video segments as one video block,these segments are assigned to a series of servers through an allocation strategy.This two-step method can not only realize the bit rate synchronization of the video segments in the same video block,but also enable the segments to be downloaded in an orderly manner.Furthermore,the client algorithm uses Q-learning method to deduce bit rate depending on different environmental state.Experimental results show that the proposed algorithm can reduce the fluctuation of video quality and improve the average video quality of the client.

Key words: Dynamic Adaptive Streaming over HTTP(DASH), multiple servers, Quality of Experience(QoE), quality oscillation, Software-Defined Network(SDN), Q-earning

摘要：

在多服务器场景下,基于HTTP的动态自适应流媒体在传输过程中,由于用户请求的高度动态性及多服务器传输带宽的差异性,客户端获取的视频质量波动较频繁,影响到用户体验质量。针对上述问题,提出一种基于软件定义网络的视频分片请求调度算法。将多个分片组成一个视频块,利用分配策略把这多个分片分配至多个服务器,实现同一视频块内视频分片的码率同步,并使分片有序下载。同时,客户端算法采用Q学习方法,根据不同的环境状态决策出相应的码率。仿真实验结果表明,该算法可减少视频质量的波动,提高客户端平均视频质量。

关键词: 基于HTTP的动态自适应流媒体, 多服务器, 体验质量, 质量波动, 软件定义网络, Q学习

CLC Number:

TP301.6

WU Ruliang,WANG Zilei,XI Hongsheng. A DASH Client Optimization Algorithm Based on Multiple Servers[J]. Computer Engineering, 2018, 44(11): 306-312.

吴如亮,王子磊,奚宏生. 一种基于多服务器的DASH客户端优化算法[J]. 计算机工程, 2018, 44(11): 306-312.

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References

［1］Cisco.The Zettabyte era:trends and analysis［EB/OL］.［2017-09-10］.https://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/vni-hyperconnectivity-wp.html.
［2］STOCKHAMMER T.Dynamic adaptive streaming over HTTP--:standards and design principles［C］//Proceedings of the 2nd Annual ACM Conference on Multimedia Systems.New York,USA:ACM Press,2011:133-144.
［3］JIANG J,SEKAR V,ZHANG H.Improving fairness,efficiency,and stability in HTTP-based adaptive video streaming with festive［C］//Proceedings of the 8th International Conference on Emerging Networking Experi-ments and Technologies.New York,USA:ACM Press,2014:97-108.
［4］PU W,ZOU Z,CHEN C W.Dynamic adaptive streaming over HTTP from multiple content distribution servers［C］//Proceedings of Global Telecommunications Conference.Washington D.C.,USA:IEEE Press,2011:1-5.
［5］ZHANG S,LI B,LI B.Presto:towards fair and efficient HTTP adaptive streaming from multiple servers［C］//Proceedings of IEEE International Conference on Communications.Washington D.C.,USA:IEEE Press,2015:6849-6854.
［6］McKEOWN N,ANDERSON T,BALAKRISHNAN H,et al.OpenFlow:enabling innovation in campus networks［J］.ACM SIGCOMM Computer Communication Review,2008,38(2):69-74.
［7］曹荣珍.基于 OpenFlow 的视频用户 QoE 优化研究［D］.北京:北京交通大学,2016.
［8］BOUTEN N,CLAEYS M,VAN POECKE B,et al.Dynamic server selection strategy for multi-server HTTP adaptive streaming services［C］//Proceedings of the 12th International Conference on Network and Service Management.Hong Kong,China:［s.n.］,2016:82-90.
［9］LIU L,ZHOU C,ZHANG X,et al.Probabilistic chunk scheduling approach in parallel multiple-server DASH［C］//Proceedings of Visual Communications and Image Processing Conference.Washington D.C.,USA:IEEE Press,2014:5-8.
［10］左青云,陈鸣,赵广松,等.基于 OpenFlow 的 SDN 技术研究［J］.软件学报,2013,24(5):1078-1097.
［11］WATKINS C J,DAYAN P.Q-learning［J］.Machine Learning,1992,8(3/4):279-292.
［12］CLAEYS M,LATR S,FAMAEY J,et al.Design of a Q-learning-based client quality selection algorithm for HTTP adaptive video streaming［C］//Proceedings of Adaptive and Learning Agents Workshop.Saint Paul,USA:［s.n.］,2013:30-37.
［13］KAELBLING L P,LITTMAN M L,MOORE A W.Reinforcement learning:a survey［J］.Journal of artificial intelligence research,1996,4:237-285.
［14］MOK R K,CHAN E W,CHANG R K.Measuring the quality of experience of HTTP video streaming［C］//Proceedings of IFIP/IEEE International Symposium on Integrated Network Management.Washington D.C.,USA:IEEE Press,2011:485-492.
［15］NEMETHOVA O,RIES M,ZAVODSKY M,et al.PSNR-based estimation of subjective time-variant video quality for mobiles［EB/OL］.［2017-09-10］.https://pdfs.semanticscholar.org/a496/411a16b59c265c53aa07de11a9c32ec90f65.pdf.

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