TY - GEN
T1 - Experimental Study of Video Fusion for Multi-View Video Streaming in Mobile Media Cloud
AU - Wang, Jie
AU - Yang, Shuquan
AU - Zhang, Weizhan
AU - Liu, Junquan
AU - Kong, Xie
AU - Zheng, Qinghua
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/4/26
Y1 - 2018/4/26
N2 - Nowadays, mobile users are not just content with a quick access to Internet when they are watching various types of videos, but also expecting a better video viewing experience. The reality is that decoding videos will consume very large resources of mobile devices. However, the resources of mobile devices are limited in terms of CPU, the main memory and so on, which impedes the performance enhancement. Fortunately, the emergence of mobile media cloud makes it possible to lighten decoding load on mobile devices. Cloud computing has an outstanding performance in rendering diverse services, strong computation ability, and great storage capacity in a relatively lower cost, which provides an effective channel out for the present dilemma. In this paper, we focus on the experimental study of video fusion method for multi-view video streaming under mobile media cloud environment. Firstly, we conduct a large quantity of collection experiments and find that decoding load of videos follows the power function model, which demonstrates that video fusion of multi-view videos at cloud side may effectively reduce the CPU usage of decoding at mobile side. Secondly, we further quantify the condition when the video fusion method can reduce the CPU usage of mobile devices along with its corresponding reduction rates.
AB - Nowadays, mobile users are not just content with a quick access to Internet when they are watching various types of videos, but also expecting a better video viewing experience. The reality is that decoding videos will consume very large resources of mobile devices. However, the resources of mobile devices are limited in terms of CPU, the main memory and so on, which impedes the performance enhancement. Fortunately, the emergence of mobile media cloud makes it possible to lighten decoding load on mobile devices. Cloud computing has an outstanding performance in rendering diverse services, strong computation ability, and great storage capacity in a relatively lower cost, which provides an effective channel out for the present dilemma. In this paper, we focus on the experimental study of video fusion method for multi-view video streaming under mobile media cloud environment. Firstly, we conduct a large quantity of collection experiments and find that decoding load of videos follows the power function model, which demonstrates that video fusion of multi-view videos at cloud side may effectively reduce the CPU usage of decoding at mobile side. Secondly, we further quantify the condition when the video fusion method can reduce the CPU usage of mobile devices along with its corresponding reduction rates.
KW - mobile media cloud
KW - multi view video streaming
KW - optimization conditions
KW - video fusion
UR - https://www.scopus.com/pages/publications/85049574107
U2 - 10.1109/MobileCloud.2018.00020
DO - 10.1109/MobileCloud.2018.00020
M3 - 会议稿件
AN - SCOPUS:85049574107
T3 - Proceedings - 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2018
SP - 79
EP - 86
BT - Proceedings - 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2018
Y2 - 26 March 2018 through 29 March 2018
ER -