Full Text:   <1046>

Summary:  <356>

CLC number: 

On-line Access: 2022-01-24

Received: 2021-06-30

Revision Accepted: 2022-04-22

Crosschecked: 2021-09-14

Cited: 0

Clicked: 2197

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Tian DANG

https://orcid.org/0000-0002-9589-6967

Chenxi LIU

https://orcid.org/0000-0002-9134-1235

-   Go to

Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2022 Vol.23 No.1 P.73-85

http://doi.org/10.1631/FITEE.2100308


Joint uplink and downlink resource allocation for low-latency mobile virtual reality delivery in fog radio access networks


Author(s):  Tian DANG, Chenxi LIU, Xiqing LIU, Shi YAN

Affiliation(s):  State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China

Corresponding email(s):   tiandang@bupt.edu.cn, chenxi.liu@bupt.edu.cn, liuxiqing@bupt.edu.cn, yanshi01@bupt.edu.cn

Key Words:  Virtual reality delivery, Fog radio access network (F-RAN), Round-trip latency, Resource allocation


Tian DANG, Chenxi LIU, Xiqing LIU, Shi YAN. Joint uplink and downlink resource allocation for low-latency mobile virtual reality delivery in fog radio access networks[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(1): 73-85.

@article{title="Joint uplink and downlink resource allocation for low-latency mobile virtual reality delivery in fog radio access networks",
author="Tian DANG, Chenxi LIU, Xiqing LIU, Shi YAN",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="23",
number="1",
pages="73-85",
year="2022",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2100308"
}

%0 Journal Article
%T Joint uplink and downlink resource allocation for low-latency mobile virtual reality delivery in fog radio access networks
%A Tian DANG
%A Chenxi LIU
%A Xiqing LIU
%A Shi YAN
%J Frontiers of Information Technology & Electronic Engineering
%V 23
%N 1
%P 73-85
%@ 2095-9184
%D 2022
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2100308

TY - JOUR
T1 - Joint uplink and downlink resource allocation for low-latency mobile virtual reality delivery in fog radio access networks
A1 - Tian DANG
A1 - Chenxi LIU
A1 - Xiqing LIU
A1 - Shi YAN
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 23
IS - 1
SP - 73
EP - 85
%@ 2095-9184
Y1 - 2022
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2100308


Abstract: 
Fog radio access networks (F-RANs), in which the fog access points are equipped with communication, caching, and computing functionalities, have been anticipated as a promising architecture for enabling virtual reality (VR) applications in wireless networks. Although extensive research efforts have been devoted to designing efficient resource allocation strategies for realizing successful mobile VR delivery in downlink, the equally important resource allocation problem of mobile VR delivery in uplink has so far drawn little attention. In this work, we investigate a mobile VR F-RAN delivery framework, where both the uplink and downlink transmissions are considered. We first characterize the round-trip latency of the system, which reveals its dependence on the communication, caching, and computation resource allocations. Based on this information, we propose a simple yet efficient algorithm to minimize the round-trip latency, while satisfying the practical constraints on caching, computation capability, and transmission capacity in the uplink and downlink. Numerical results show that our proposed algorithm can effectively reduce the round-trip latency compared with various baselines, and the impacts of communication, caching, and computing resources on latency performance are illustrated.

雾无线接入网络中面向低时延移动虚拟现实分发的联合上下行资源分配

党甜,刘晨熙,刘喜庆,闫实
北京邮电大学网络与交换技术国家重点实验室,中国北京市,100876
摘要:雾无线接入网络(F-RAN)中,雾接入节点上部署了通信、缓存和计算功能,因此,F-RAN被认为是一种可使能移动虚拟现实(VR)应用的无线网络架构。为实现移动VR分发,高效的下行资源分配策略已被广泛研究,但同样重要的VR分发上行资源分配问题至今少有关注。本文研究了基于F-RAN的移动VR分发框架,并同时考虑上行和下行传输的影响。首先,通过刻画系统往返时延,揭示了通信、缓存和计算资源的影响。在此基础上,考虑缓存和计算容量以及上行和下行链路传输容量的约束,提出一种简单高效的往返时延最小化算法。仿真结果表明,与其他基准方法相比,本文所提算法可有效降低往返时延;阐明了通信、缓存和计算资源对往返时延性能的影响。

关键词:虚拟现实分发;雾无线接入网络;往返时延;资源分配

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Bastug E, Bennis M, Medard M, et al., 2017. Toward interconnected virtual reality: opportunities, challenges, and enablers. IEEE Commun Mag, 55(6):110-117. doi: 10.1109/MCOM.2017.1601089

[2]Boyd S, Mattingley J, 2018. Branch and Bound Methods. Stanford University, Stanford, USA.

[3]Chen MZ, Semiari O, Saad W, et al., 2020. Federated echo state learning for minimizing breaks in presence in wireless virtual reality networks. IEEE Trans Wirel Commun, 19(1):177-191. doi: 10.1109/TWC.2019.2942929

[4]Chiu TC, Pang AC, Chung WH, et al., 2019. Latency-driven fog cooperation approach in fog radio access networks. IEEE Trans Serv Comput, 12(5):698-711. doi: 10.1109/TSC.2018.2858253

[5]Cisco System, 2019. Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2017–2020. White Paper.

[6]Dai JM, Zhang ZL, Mao SW, et al., 2020. A view synthesis-based 360° VR caching system over MEC-enabled C-RAN. IEEE Trans Circ Syst Video Technol, 30(10):3843-3855. doi: 10.1109/TCSVT.2019.2946755

[7]Dang T, Peng MG, 2019. Joint radio communication, caching, and computing design for mobile virtual reality delivery in fog radio access networks. IEEE J Sel Areas Commun, 37(7):1594-1607. doi: 10.1109/JSAC.2019.2916486

[8]Du JB, Yu FR, Lu GY, et al., 2020. MEC-assisted immersive VR video streaming over terahertz wireless networks: a deep reinforcement learning approach. IEEE Int Things J, 7(10):9517-9529. doi: 10.1109/JIOT.2020.3003449

[9]Hu FH, Deng YS, Saad W, et al., 2020. Cellular-connected wireless virtual reality: requirements, challenges, and solutions. IEEE Commun Mag, 58(5):105-111. doi: 10.1109/MCOM.001.1900511

[10]Huang HC, Liu B, Chen L, et al., 2018. D2D-assisted VR video pre-caching strategy. IEEE Access, 6: 61886-61895. doi: 10.1109/ACCESS.2018.2868766

[11]Liu YM, Yu FR, Li X, et al., 2018. Distributed resource allocation and computation offloading in fog and cloud networks with non-orthogonal multiple access. IEEE Trans Veh Technol, 67(12):12137-12151. doi: 10.1109/TVT.2018.2872912

[12]Nelder JA, Mead R, 1965. A simplex method for function minimization. Comput J, 7(4):308-313. doi: 10.1093/comjnl/7.4.308

[13]Park J, Popovski P, Simeone O, 2018. Minimizing latency to support VR social interactions over wireless cellular systems via bandwidth allocation. IEEE Wirel Commun Lett, 7(5):776-779. doi: 10.1109/LWC.2018.2823761

[14]Park SH, Simeone O, Shitz SS, 2016. Joint optimization of cloud and edge processing for fog radio access networks. IEEE Trans Wirel Commun, 15(11):7621-7632. doi: 10.1109/TWC.2016.2605104

[15]Peng MG, Yan S, Zhang KC, et al., 2016. Fog-computing-based radio access networks: issues and challenges. IEEE Netw, 30(4):46-53. doi: 10.1109/MNET.2016.7513863

[16]Sun YP, Chen ZY, Tao MX, et al., 2019. Communications, caching, and computing for mobile virtual reality: modeling and tradeoff. IEEE Trans Commun, 67(11):7573-7586. doi: 10.1109/TCOMM.2019.2920594

[17]Yoshihara T, Fujita S, 2019. Fog-assisted virtual reality MMOG with ultra low latency. 7th Int Symp on Computing and Networking, p.121-129. doi: 10.1109/CANDAR.2019.00022

[18]You D, Doan TV, Torre R, et al., 2019. Fog computing as an enabler for immersive media: service scenarios and research opportunities. IEEE Access, 7:65797-65810. doi: 10.1109/ACCESS.2019.2917291

[19]Zhang P, Peng MG, Cui SG, et al., 2022. Theory and techniques for "intellicise" wireless networks. Front Inform Technol Electron Eng, 23(1):1-4. doi: 10.1631/FITEE.2210000

[20]Zhang Y, Jiao L, Yan JY, et al., 2019. Dynamic service placement for virtual reality group gaming on mobile edge cloudlets. IEEE J Sel Areas Commun, 37(8):1881-1897. doi: 10.1109/JSAC.2019.2927071

[21]Zhou Y, Pan CH, Yeoh PL, et al., 2021. Communication-and-computing latency minimization for UAV-enabled virtual reality delivery systems. IEEE Trans Commun, 69(3):1723-1735. doi: 10.1109/TCOMM.2020.3040283

[22]Zipf GK, 1929. Relative Frequency as a Determinant of Phonetic Change. PhD Thesis, Harvard University, Cambridge, USA.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2022 Journal of Zhejiang University-SCIENCE