Energy-efficient predictive HTTP adaptive streaming in mobile cellular networks

Tao，Liqiang1,2; Gong，Yi1; Jin，Shi2; Zhao，Junhui3

10.1109/WCNC.2018.8377424

2018-06-08

1525-3511

978-1-5386-1735-9

IEEE Wireless Communications and Networking Conference, WCNC

2018-April

11

1-6

15-18 April 2018

Barcelona, Spain

Predictive green streaming have recently gained attention in wireless network literature due to its significant energy-savings and quality of experience (QoE) gains. In this paper, we investigate how predicted user rates can be exploited for mobile video streaming with the popular Hypertext Transfer Protocol (HTTP) [e.g., HTTP adaptive streaming (HAS)]. To this end, we develop a stochastic predictive HTTP Adaptive streaming (PHAS) optimization framework to achieve the following objectives: 1) an edge-cloud assisted framework for prediction based HAS and identify its key functional entities and their interactions; 2) modelling uncertainty in predicted user rates and propose a robust two-stage QoE optimization approach which dynamically allocate the risks and optimize system efficiency over a time horizon; 3) an efficient heuristic algorithm allocating time slot ratio for multi-users to improve the network efficiency, fairness and overall QoE under different prediction error variances, wireless link conditions and buffer length constraints; Simulation studies and analytical results show that our method has a better performance than traditional methods in terms of average QoE, fairness and energy efficiency.

Quality of experience Streaming media Optimization Wireless communication Predictive models Radio frequency Conferences

第一

英语

EI

20182705393213

Mobile telecommunication systems ; Optimization ; Hypertext systems ; Stochastic systems ; Heuristic algorithms ; Heuristic methods ; Uncertainty analysis ; Risk assessment ; Wireless networks ; Energy efficiency ; Quality of service

Energy Conservation:525.2 ; Radio Systems and Equipment:716.3 ; Data Communication, Equipment and Techniques:722.3 ; Computer Programming:723.1 ; Control Systems:731.1 ; Accidents and Accident Prevention:914.1 ; Optimization Techniques:921.5 ; Probability Theory:922.1 ; Systems Science:961

2-s2.0-85049158810

ENGINEERING

Scopus

1.Department of Electrical and Electronic Engineering, Southern University of Science and Technology, ,China
2.National Mobile Communications Research Laboratory, Southeast University, ,China
3.School of Electronic and Information Engineering, Beijing Jiaotong University, ,China

Tao，Liqiang,Gong，Yi,Jin，Shi,et al. Energy-efficient predictive HTTP adaptive streaming in mobile cellular networks[C],2018:1-6.