Energy-efficient HTTP Adaptive Streaming with Anticipated Channel Throughput Prediction in Wireless Networks

Tao, Liqiang1; Gong, Yi2; Jin, Shi3; Zhao, Junhui4

10.1145/3127540.3127574

2017

PROCEEDINGS OF THE 20TH ACM INTERNATIONAL CONFERENCE ON MODELLING, ANALYSIS AND SIMULATION OF WIRELESS AND MOBILE SYSTEMS (MSWIM'17)

2017-November

253-258

Miami, FL, United states

1515 BROADWAY, NEW YORK, NY 10036-9998 USA

ASSOC COMPUTING MACHINERY

Exploiting predicted channel information and designing energy-efficient content delivery protocols has started to draw attention, which is referred to as predictive, anticipatory, or context-aware resource allocation. In this paper, we investigate how predicted user rates can be exploited for streaming on-demand mobile video with dynamic adaptive streaming over HTTP(DASH). Specifically, we propose an edge-cloud assisted framework for prediction based DASH streaming; For optimal prediction scenario, we propose a lightweight algorithm to solve it; For imperfect prediction scenario, we model uncertainty in predicted user rates and propose a chance constraint programming method to dynamically allocate the risks, optimize QoE and system efficiency; For the multi-user scenario, we propose a quality-level-aware throughput gain maximization method to improve the network efficiency, fairness and QoE for all users under different prediction error variances; Simulation studies show that our method has a better performance than traditional methods in terms of average QoE, fairness and energy efficiency.

mobility assisted channel throughput prediction radio access network energy efficiency video streaming DASH

第一 ; 通讯

英语

CPCI-S ; EI

Shenzhen Peacock Program[KQJSCX20160226193545]

Computer Science ; Engineering ; Telecommunications

Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Telecommunications

WOS:000440745600034

20183005595453

Computer programming ; Constraint theory ; Distributed computer systems ; Forecasting ; Green computing ; HTTP ; Risk perception ; Throughput ; Uncertainty analysis ; Video streaming ; Wireless networks

Energy Conservation:525.2 ; Data Communication, Equipment and Techniques:722.3 ; Digital Computers and Systems:722.4 ; Computer Programming:723.1 ; Accidents and Accident Prevention:914.1 ; Probability Theory:922.1 ; Systems Science:961

Web of Science

1.Southeast Univ, Southern Univ Sci & Technol, Nanjing, Jiangsu, Peoples R China
2.Southern Univ Sci & Technol, Dept Elect & Elect Engn, Shenzhen, Peoples R China
3.Southeast Univ, Nanjing, Jiangsu, Peoples R China
4.Beijing Jiaotong Univ, Beijing, Peoples R China

Tao, Liqiang,Gong, Yi,Jin, Shi,et al. Energy-efficient HTTP Adaptive Streaming with Anticipated Channel Throughput Prediction in Wireless Networks[C]. 1515 BROADWAY, NEW YORK, NY 10036-9998 USA:ASSOC COMPUTING MACHINERY,2017:253-258.