AMVP-Cloud: A Framework of Adaptive Mobile Video Streaming and User Behavior Oriented Video Pre-fetching in the Clouds

2012 ◽  
Author(s):  
Bin Pan ◽  
Xiaofei Wang ◽  
Chung-Pyo Hong ◽  
Shin-Dug Kim
Keyword(s):  
Video Streaming ◽  
User Behavior ◽  
Mobile Video ◽  
Mobile Video Streaming

scholarly journals Toward Cost-Effective Mobile Video Streaming through Environment-Aware Watching State Prediction

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3654 ◽  
Author(s):  
Xuanyu Wang ◽  
Weizhan Zhang ◽  
Xiang Gao ◽  
Jingyi Wang ◽  
Haipeng Du ◽  
...  
Keyword(s):  
Power Consumption ◽  
Video Streaming ◽  
Data Transmission ◽  
Physical Environment ◽  
Time Window ◽  
User Behavior ◽  
Cost Effective ◽  
Mobile Video ◽  
Data Usage ◽  
Mobile Video Streaming

Mobile video applications are becoming increasingly prevalent and enriching the way people learn and are entertained. However, on mobile terminals with inherently limited resources, mobile video streaming services consume too much energy and bandwidth, which is an urgent problem to solve. At present, research on cost-effective mobile video streaming typically focuses on the management of data transmission. Among such studies, some new approaches consider the user’s behavior to further optimize data transmission. However, these studies have not adequately discussed the specific impact of the physical environment on user behavior. Therefore, this paper takes into account the environment-aware watching state and proposes a cost-effective mobile video streaming scheme to reduce power consumption and mobile data usage. First, the watching state is predicted by machine learning based on user behavior and the physical environment during a given time window. Second, based on the resulting prediction, a downloading algorithm is introduced based on the user equipment (UE) running mode in the LTE system and the VLC player. Finally, according to the corresponding experimental results obtained in a real-world environment, the proposed approach, compared to its benchmarks, effectively reduces the data usage (14.4% lower than that of energy-aware, on average) and power consumption (about 19% when there are screen touches) of mobile devices.

Optimal Pricing for Mobile Video Streaming in 3G Wireless Packet Networks

2012 ◽  
Vol 2 (2) ◽  
pp. 134-136
Author(s):  
Ch. Divya Ch. Divya ◽  
◽  
Dr. P. Govardhan Dr. P. Govardhan
Keyword(s):  
Video Streaming ◽  
Optimal Pricing ◽  
Packet Networks ◽  
Mobile Video ◽  
Mobile Video Streaming ◽  
Wireless Packet

scholarly journals QoE-Traffic Optimization Through Collaborative Edge Caching in Adaptive Mobile Video Streaming

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 52261-52276 ◽  
Author(s):  
Abbas Mehrabi ◽  
Matti Siekkinen ◽  
Antti Yla-Jaaski
Keyword(s):  
Video Streaming ◽  
Mobile Video ◽  
Mobile Video Streaming ◽  
Traffic Optimization ◽  
Edge Caching

scholarly journals CBM: Online Strategies on Cost-Aware Buffer Management for Mobile Video Streaming

2014 ◽  
Vol 16 (1) ◽  
pp. 242-252 ◽  
Author(s):  
Jian He ◽  
Zheng Xue ◽  
Di Wu ◽  
Dapeng Oliver Wu ◽  
Yonggang Wen
Keyword(s):  
Video Streaming ◽  
Buffer Management ◽  
Mobile Video ◽  
Mobile Video Streaming ◽  
Online Strategies

User-adaptive mobile video streaming

2012 ◽  
Author(s):  
Yuriy Reznik ◽  
Ed Asbun ◽  
Zhifeng Chen ◽  
Yan Ye ◽  
Eldad Zeira ◽  
...  
Keyword(s):  
Video Streaming ◽  
Mobile Video ◽  
Mobile Video Streaming
Sign in / Sign up

Export Citation Format

Share Document