Traffic evaluation and modeling for spatio-temporal slicing based VR panoramic video transmission

Shengqian HAN; Han LOU; Junlai WANG

doi:10.11959/j.issn.1000-436x.2022139

您当前的位置：

首页 >

文章列表页 >

Traffic evaluation and modeling for spatio-temporal slicing based VR panoramic video transmission

Papers | 更新时间：2024-06-05

- Traffic evaluation and modeling for spatio-temporal slicing based VR panoramic video transmission
- Journal on Communications Vol. 43, Issue 7, Pages: 102-112(2022)
- 作者机构：
  
  北京航空航天大学电子信息工程学院，北京 100191
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61871015)
- DOI：10.11959/j.issn.1000-436x.2022139
  CLC： TN92
- Online First：2022-06，
  
  Published：25 July 2022
- 稿件说明：
移动端阅览
Shengqian HAN, Han LOU, Junlai WANG. Traffic evaluation and modeling for spatio-temporal slicing based VR panoramic video transmission[J]. Journal on Communications, 2022, 43(7): 102-112.
DOI：

Shengqian HAN, Han LOU, Junlai WANG. Traffic evaluation and modeling for spatio-temporal slicing based VR panoramic video transmission[J]. Journal on Communications, 2022, 43(7): 102-112. DOI： 10.11959/j.issn.1000-436x.2022139.

摘要

为了刻画虚拟现实（VR）全景视频的传输流量需求，针对时空切片传输模式，首先，基于VR全景视频观看数据集，对传输流量评估与空间切块方式和时间分段方式之间的关系进行仿真。然后，基于仿真结果，对VR 全景视频的传输流量进行统计建模，建立传输流量与空间切块数量和时间分段长度之间的函数关系。最后，基于得到的传输流量模型，提出一种VR全景视频时空切片方式的嵌套优化方法，其外层对空间切块数量进行遍历寻优，内层直接计算最优的时间分段长度。研究和仿真结果表明，传输流量近似服从正态分布，其均值和方差与时空切片方式有关；通过对不同类型的视频分别进行传输流量统计建模，基于所建立的流量模型优化得到的时空切片方式与通过仿真搜索得到的最优切片方式性能接近。

Abstract

To characterize the traffic load of virtual reality (VR) panoramic video under the spatio-temporal slicing transmission mode

firstly

based on a real-word VR video viewing dataset

the relationship between the traffic load and the spatio-temporal slicing strategy was evaluated via simulations.Secondly

on the basis of the simulation results

a statistical traffic model was established

describing the interaction between the traffic load and the number of spatial tiles as well as the duration of temporal chunks.Finally

based on the established model

a hierarchical spatial-temporal slicing strategy optimization method was proposed

where the outer layer found the optimal number of spatial tiles by exhaustive searching while the inner layer could directly compute the optimal duration of temporal chunks.Research and simulation results show that the traffic load approximately follows a normal distribution

where the mean and variance are functions of the spatio-temporal slicing strategy.By establishing the traffic model for each type of videos

the optimized slicing strategy based on the established model performs close to the optimal strategy obtained by searching by simulations.

关键词

Keywords

references

华为iLab . 面向VR业务的承载网络需求白皮书 [R ] . 2016 .

HUAWEI iLab . White paper on bearer network requirements for VR services [R ] . 2016 .

3GPP . Virtual reality (VR) media services over 3GPP:TR 26.918 [S ] . 2017 .

ZINK M , SITARAMAN R , NAHRSTEDT K . Scalable 360° video stream delivery:challenges,solutions,and opportunities [J ] . Proceedings of the IEEE , 2019 , 107 ( 4 ): 639 - 650 .

HOSSEINI M , SWAMINATHAN V . Adaptive 360 VR video streaming based on MPEG-DASH SRD [C ] // Proceedings of 2016 IEEE International Symposium on Multimedia . Piscataway:IEEE Press , 2016 : 407 - 408 .

GADDAM V R , RIEGLER M , EG R , et al . Tiling in interactive panoramic video:approaches and evaluation [J ] . IEEE Transactions on Multimedia , 2016 , 18 ( 9 ): 1819 - 1831 .

MISRA K , SEGALL A , HOROWITZ M , et al . An overview of tiles in HEVC [J ] . IEEE Journal of Selected Topics in Signal Processing , 2013 , 7 ( 6 ): 969 - 977 .

ALFACE P R , MACQ J F , VERZIJP N . Interactive omnidirectional video delivery:a bandwidth-effective approach [J ] . Bell Labs Technical Journal , 2012 , 16 ( 4 ): 135 - 147 .

ZARE A , AMINLOU A , HANNUKSELA M M , et al . HEVC-compliant tile-based streaming of panoramic video for virtual reality applications [C ] // Proceedings of the 24th ACM International Conference on Multimedia . New York:ACM Press , 2016 : 601 - 605 .

TU Z Z , ZONG T Y , XI X L , et al . Content adaptive tiling method based on user access preference for streaming panoramic video [C ] // Proceedings of 2018 IEEE International Conference on Consumer Electronics . Piscataway:IEEE Press , 2018 : 1 - 4 .

NGUYEN D V , TRAN H T T , THANG T C . An evaluation of tile selection methods for viewport-adaptive streaming of 360-degree video [J ] . ACM Transactions on Multimedia Computing,Communications,and Applications , 2020 , 16 ( 1 ): 1 - 24 .

SINGLA A , GÖRING S , RAAKE A , et al . Subjective quality evaluation of tile-based streaming for omnidirectional videos [C ] // Proceedings of the 10th ACM Multimedia Systems Conference . New York:ACM Press , 2019 : 232 - 242 .

AN C L , YEN S C , HUANG C Y , et al . On the optimal encoding ladder of tiled 360° videos for head-mounted virtual reality [J ] . IEEE Transactions on Circuits and Systems for Video Technology , 2021 , 31 ( 4 ): 1632 - 1647 .

CHEN X L , WU D , AHMAD I . Optimized viewport-adaptive 360-degree video streaming [J ] . CAAI Transactions on Intelligence Technology , 2021 , 6 ( 3 ): 347 - 359 .

BETHANABHOTLA D , CAIRE G , NEELY M J . WiFlix:adaptive video streaming in massive MU-MIMO wireless networks [J ] . IEEE Transactions on Wireless Communications , 2016 , 15 ( 6 ): 4088 - 4103 .

HAN S Q , SU H T , YANG C Y , et al . Proactive edge caching for video on demand with quality adaptation [J ] . IEEE Transactions on Wireless Communications , 2020 , 19 ( 1 ): 218 - 234 .

SUN Y P , CHEN Z Y , TAO M X , et al . Communications,caching,and computing for mobile virtual reality:modeling and tradeoff [J ] . IEEE Transactions on Communications , 2019 , 67 ( 11 ): 7573 - 7586 .

WEI X , YANG C Y , HAN S Q . Prediction,communication,and computing duration optimization for VR video streaming [J ] . IEEE Transactions on Communications , 2021 , 69 ( 3 ): 1947 - 1959 .

XU M , LI C , ZHANG S Y , et al . State-of-the-art in 360° video/image processing:perception,assessment and compression [J ] . IEEE Journal of Selected Topics in Signal Processing , 2020 , 14 ( 1 ): 5 - 26 .

WU C L , TAN Z H , WANG Z , et al . A dataset for exploring user behaviors in VR spherical video streaming [C ] // Proceedings of the 8th ACM on Multimedia Systems Conference . New York:ACM Press , 2017 : 193 - 198 .

YAQOOB A , MUNTEAN G M . A combined field-of-view prediction-assisted viewport adaptive delivery scheme for 360° videos [J ] . IEEE Transactions on Broadcasting , 2021 , 67 ( 3 ): 746 - 760 .

BAN Y X , XIE L , XU Z M , et al . CUB360:exploiting cross-users behaviors for viewport prediction in 360 video adaptive streaming [C ] // Proceedings of 2018 IEEE International Conference on Multimedia and Expo . Piscataway:IEEE Press , 2018 : 1 - 6 .

XIE L , ZHANG X G , GUO Z M . CLS:a cross-user learning based system for improving QoE in 360-degree video adaptive streaming [C ] // Proceedings of the 26th ACM International Conference on Multimedia . New York:ACM Press , 2018 : 564 - 572 .

ZHANG Y X , ZHAO P Y , BIAN K G , et al . DRL360:360-degree video streaming with deep reinforcement learning [C ] // Proceedings of IEEE Conference on Computer Communications . Piscataway:IEEE Press , 2019 : 1252 - 1260 .

NGUYEN A , YAN Z S , NAHRSTEDT K . Your attention is unique:detecting 360-degree video saliency in head-mounted display for head movement prediction [C ] // Proceedings of the 26th ACM International Conference on Multimedia . New York:ACM Press , 2018 : 1190 - 1198 .

FFMPEG Team . FFmpeg software [EB ] . 2022 .

RICHARDSON I E . G.H.264/MPEG-4 part 10 white paper [R ] . 2003 .

BENTO4 . Bento4 MP4,DASH,HLS,CMAF SDK and tools [EB ] . 2020 .

PERFECTO C , ELBAMBY M S , SER J D , et al . Taming the latency in multi-user VR 360°:a QoE-aware deep learning-aided multicast framework [J ] . IEEE Transactions on Communications , 2020 , 68 ( 4 ): 2491 - 2508 .

FEI Z S , WANG F , WANG J , et al . QoE evaluation methods for 360-degree VR video transmission [J ] . IEEE Journal of Selected Topics in Signal Processing , 2020 , 14 ( 1 ): 78 - 88 .

ZHENG C , LIU S H , HUANG Y M , et al . Hybrid policy learning for energy-latency tradeoff in MEC-assisted VR video service [J ] . IEEE Transactions on Vehicular Technology , 2021 , 70 ( 9 ): 9006 - 9021 .

Views

1702

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Virtual reality compressing and transmitting system based on mobile edge computing

Industrial intelligent network: deepening and upgrading of industrial Internet

Capacity analysis of the MEO satellite constellation

Traffic model for wireless mesh networks by statistical networks calculus

Related Author

Bin TAN

Songyuan ZHAO

Jun WU

Wenru ZHANG

Ping ZHANG

Huiyong LIU

Wenjing LI

Fanqin ZHOU

Related Institution

College of Electronics and Information Engineering,Jinggangshan University,Ji’an

College of Electronics and Information Engineering,Tongji University

School of Computer and Technology, Fudan University

School of Computer and Technology,Fudan University,Shanghai 200433,China 4.Guangdong Communications ＆Networks Institute

State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications

AI问答

⁰