Delay-Sensitive Video Computing in the Cloud: A Survey

被引：24
|
作者：
Abdallah, Maha [1 ]
Griwodz, Carsten [2 ,3 ]
Chen, Kuan-Ta [4 ]
Simon, Gwendal [5 ]
Wang, Pin-Chun [6 ]
Hsu, Cheng-Hsin [6 ]
机构：
[1] Sorbonne Univ, CNRS, Lab Informat Paris 6, 4 Pl Jussieu, F-75005 Paris, France
[2] Univ Oslo, Gaustadalleen 23, N-0371 Oslo, Norway
[3] Simula Res Lab, Martin Linges Vei 25, N-1325 Lysaker, Norway
[4] Acad Sinica, 128,Sect 2,Acad Rd, Taipei 11529, Taiwan
[5] IMT Atlantique, 2 Rue Chataigneraie, F-35510 Cesson Sevigne, France
[6] Natl Tsing Hua Univ, 101 Sect 2 Kuang Fu Rd, Hsinchu 300, Taiwan
来源：
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS | 2018年 / 14卷 / 03期
关键词：
Multimedia; cloud computing; virtualization; optimization; networking; latency; quality of experience (QoE); quality of service (QoS); applications; architecture; SERVICE; ALGORITHMS; LATENCY; SYSTEM; CACHE; ART;
D O I：
10.1145/3212804
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
While cloud servers provide a tremendous amount of resources for networked video applications, most successful stories of cloud-assisted video applications are presentational video services, such as YouTube and NetFlix. This article surveys the recent advances on delay-sensitive video computations in the cloud, which are crucial to cloud-assisted conversational video services, such as cloud gaming, Virtual Reality (VR), Augmented Reality (AR), and telepresence. Supporting conversational video services with cloud resources is challenging because most cloud servers are far away from the end users while these services incur the following stringent requirements: high bandwidth, short delay, and high heterogeneity. In this article, we cover the literature with a top-down approach: from applications and experience, to architecture and management, and to optimization in and outside of the cloud. We also point out major open challenges, hoping to stimulate more research activities in this emerging and exciting direction.
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页数：29
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