Journal of Guangxi Normal University(Natural Science Edition) ›› 2021, Vol. 39 ›› Issue (5): 147-157.doi: 10.16088/j.issn.1001-6600.2020111201

Previous Articles     Next Articles

Determination of Video Streaming Buffer Threshold Constrainted with Initial Delay and Hysteresis Probability

WEN Peng, WANG Yaqing, TANG Shengda*   

  1. School of Mathematics and Statistics, Guangxi Normal University, Guilin Guangxi 541006, China
  • Received:2020-11-12 Revised:2021-02-02 Online:2021-09-25 Published:2021-10-19

Abstract: This paper proposes a novel stochastic fluid model (SFM) framework to describe the IP network dynamic video streaming system. The goal is to weigh the relationship between the hysteresis probability and the initial buffer delay, and then to determine an optimal buffer threshold setting. Firstly, the Laplace-Stieltjes transform (LST) matrices of the three First Passage Times (FPTs) is derived in the video streaming system, and then the occurrence probability of the hysteresis is obtained as well as the probability that the initial buffer time is higher than the given tolerable time. Based on these results, the control optimization problem of the initial buffer threshold is further constructed, and an algorithm is designed to find the optimal buffer threshold. Finally, a numerical result is provided to confirm the theoretical findings.

Key words: video streaming system, stochastic fluid model (SFM), hysteresis probability, initial buffer delay

CLC Number: 

  • TN919.8
[1] 周个妹, 刘泽斌. 基于云服务的P2P流媒体技术在远程教学视频传输中的应用[J]. 中国教育信息化, 2016(6): 91-94.
[2] 宋瑛瑛, 刘文婧. 移动终端气象流媒体服务的研究与设计[J]. 计算机系统应用, 2014, 23(9):26-31.
[3] 白钢华, 李王辉. 网络视频流识别技术研究[J]. 信息安全与技术, 2014, 5(10): 62-64.
[4] PEREIRA R, PEREIRA E G. Video streaming: Overview and challenges in the internet of things[M]. Pervasive Computing: Next Generation Platforms for Intelligent Data Collection.London: Academic Press, 2016: 417-444.
[5] 程婕, 耿岩. 移动视频业务卡顿现象评估方法研究与演进[J]. 邮电设计技术, 2017(12): 11-15.
[6] HOßFELD T, EGGER S, SCHATZ R, et al. Initial delay vs. interruptions: Between the devil and the deep blue sea[C] // 2012 Fourth International Workshop on Quality of Multimedia Experience. Melbourne: IEEE, 2012: 1-6.
[7] SCHWIND A, MIDOGLU C, ALAY Ö, et al. Dissecting the performance of YouTube video streaming in mobile networks[J]. International Journal of Network Management, 2020, 30(3): e2058.
[8] VEILLON V, DENNINNART C, SALEHI M A. F-FDN: Federation of fog computing systems for low latency video streaming[C] // 2019 IEEE 3rd International Conference on Fog and Edge Computing (ICFEC). Larnaca: IEEE, 2019: 1-9.
[9] GUO Y S, YU F R, AN J P, et al. Buffer-aware streaming in small scale wireless networks: A deep reinforcement learning approach[J]. IEEE Transactions on Vehicular Technology, 2019, 68(7): 6891-6902.
[10] 孙盛杰, 廖宇力, 虞衍聪. 流媒体连续性与实时性的有效平衡机制[J]. 广西师范大学学报(自然科学版), 2012, 30(2): 29-34.
[11] BARMAN N, MARTINI M. QoE modeling for HTTP adaptive video streaming-A survey and open challenges[J]. IEEE Access, 2019, 7:30831-30859.
[12] BOXMA O, ZWART B. Fluid flow models in performance analysis[J]. Computer Communications, 2018, 131: 22-25.
[13] BOSMAN J, van der MEI R, NÚÑEZ-QUEIJA R. A fluid model analysis of streaming media in the presence of time-varying bandwidth[C] // 2012 24th International Teletraffic Congress (ITC 24). Krakow: IEEE, 2012: 1-8.
[14] MARTIN F I V, ALINS-DELGADO J J, AGUILAR-IGARTUA M, et al. Modelling an adaptive-rate video-streaming service using markov-rewards models[C] // First International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks. Dallas: IEEE, 2004: 92-99.
[15] BEAN N G, O′REILLY M M. A stochastic two-dimensional fluid model[J]. Stochastic Models, 2013, 29(1): 31-63.
[16] AHN S, RAMASWAMI V. Efficient algorithms for transient analysis of stochastic fluid flow models[J]. Journal of Applied Probability, 2005, 42(2): 531-549.
[17] AHN S, RAMASWAMI V. Transient analysis of fluid models via elementary level-crossing arguments[J]. Stochastic Models, 2006, 22(1): 129-147.
[18] RAMASWAMI V. Passage times in fluid models with application to risk processes[J]. Methodology and Computing in Applied Probability, 2006, 8(4): 497-515.
[19] ABATE J, WHITT W. Numerical inversion of Laplace transforms of probability distributions[J]. ORSA Journal on Computing, 1995, 7(1): 36-43.
[20] BEAN N G, O′REILLY M M, TAYLOR P G. Hitting probabilities and hitting times for stochastic fluid flows[J]. Stochastic Processes and Their Applications, 2005, 115(9): 1530-1556.
[1] LEI Yun, WANG Xian-hui, WANG Xiao-yun, SUN Ze-rui, YU Chun-qiang, ZHANG Xian-quan. An Information Hiding Method Based on JPEG Images [J]. Journal of Guangxi Normal University(Natural Science Edition), 2013, 31(4): 48-53.
[2] ZHANG Xian-quan, WANG Xian-hui, WANG Xiao-yun, YUChun-qiang. Information Hiding Algorithm for JPEG Images Based on Block [J]. Journal of Guangxi Normal University(Natural Science Edition), 2012, 30(3): 119-124.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] ZHAN Xin, CHEN Lijing, LIAO Guangfeng, LI Bing, LU Rumei. Research Progress of New C21-Steroids in Medicinal Plant of Asclepiadaceae (Ⅰ)[J]. Journal of Guangxi Normal University(Natural Science Edition), 2021, 39(5): 1 -29 .
[2] ZHAO Dongjiang, MA Songyan, TIAN Xiqiang. Applications of CoSe2/C Catalyst in Electrocatalytic Oxygen Reduction[J]. Journal of Guangxi Normal University(Natural Science Edition), 2021, 39(5): 30 -43 .
[3] GUAN Xiaojin, ZHAO Keyi, LIU Shiling, LI Yi, YU Fangming, LI Chunming, LIU Kehui. Global Trends and Hot Topics in the Field of Manganese Phytoremediation over the Past Three Decades: A Review Based on Citespace Visualization[J]. Journal of Guangxi Normal University(Natural Science Edition), 2021, 39(5): 44 -57 .
[4] LIANG Qiufang, DONG Xiaoyan, FENG Ping. Advanced in CYP2D Subfamily Genes and Evolutionary Mechanisms[J]. Journal of Guangxi Normal University(Natural Science Edition), 2021, 39(5): 58 -63 .
[5] XU Lunhui, SU Nan, PIAN Yuzhuang, LIN Peiqun. Bus Travel Time Prediction Based on Extreme Learning Machine Optimized by Artificial Bee Colony Algorithm[J]. Journal of Guangxi Normal University(Natural Science Edition), 2021, 39(5): 64 -77 .
[6] WENG Xiaoxiong, XIE Zhipeng. Study on Freeway Nodes Importance Based on Multilayer Complex Network[J]. Journal of Guangxi Normal University(Natural Science Edition), 2021, 39(5): 78 -88 .
[7] WU Kangkang, ZHU Xufei, LU Ye, ZHOU Peng, DONG Cui, DAI Qinxuan, ZHOU Runchang. LS-FIR Filter Based on Least Square Method[J]. Journal of Guangxi Normal University(Natural Science Edition), 2021, 39(5): 89 -99 .
[8] HAI Tao, LI Nana, ZHOU Wenjie, CHEN Juan, SONG Min. Design of Intelligent Monitoring System for Photovoltaic Greenhouse Based on LPWAN Internet of Things[J]. Journal of Guangxi Normal University(Natural Science Edition), 2021, 39(5): 100 -109 .
[9] LI Bing, LI Zhi, YANG Yilong. Classification of Non-Functional Software Requirements Using Word Embeddings and Long Short-Term Memory[J]. Journal of Guangxi Normal University(Natural Science Edition), 2021, 39(5): 110 -121 .
[10] WU Lingyu, LAN Yang, XIA Haiying. Retinal Image Registration Using Convolutional Neural Network[J]. Journal of Guangxi Normal University(Natural Science Edition), 2021, 39(5): 122 -133 .