TY - GEN
T1 - Energy-Efficient and QoE-Aware 360-Degree Video Streaming on Mobile Devices
AU - Chen, Xianda
AU - Cao, Guohong
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Tile-based streaming has been widely used in 360° video streaming to adapt to varying network conditions. However, downloading and processing many small tiles consumes a large amount of energy on mobile devices. To address this issue, we propose techniques to encode video by considering the viewing popularity, where the tiles requested by users of similar interests are encoded as a large tile (called Ptile). When encoding Ptiles, we propose to further save energy by reducing the insignificant frames in each video segment, i.e., reducing the frame rate to save energy while satisfying some QoE constraint. Based on real video traces, we model the impact of video features (i.e., video bitrate, frame rate) and user behavior (i.e., view switching) on QoE, and model the impact of video features on power consumption. Based on the QoE model and the power model, we formulate the energy-efficient and QoE-aware 360° video streaming problem as an optimization problem, and propose a control theory based algorithm to solve it. Through extensive evaluations based on real traces, we demonstrate that the proposed algorithm can significantly reduce the energy consumption (49.7%) and improve the QoE (7.4%).
AB - Tile-based streaming has been widely used in 360° video streaming to adapt to varying network conditions. However, downloading and processing many small tiles consumes a large amount of energy on mobile devices. To address this issue, we propose techniques to encode video by considering the viewing popularity, where the tiles requested by users of similar interests are encoded as a large tile (called Ptile). When encoding Ptiles, we propose to further save energy by reducing the insignificant frames in each video segment, i.e., reducing the frame rate to save energy while satisfying some QoE constraint. Based on real video traces, we model the impact of video features (i.e., video bitrate, frame rate) and user behavior (i.e., view switching) on QoE, and model the impact of video features on power consumption. Based on the QoE model and the power model, we formulate the energy-efficient and QoE-aware 360° video streaming problem as an optimization problem, and propose a control theory based algorithm to solve it. Through extensive evaluations based on real traces, we demonstrate that the proposed algorithm can significantly reduce the energy consumption (49.7%) and improve the QoE (7.4%).
UR - http://www.scopus.com/inward/record.url?scp=85140917776&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85140917776&partnerID=8YFLogxK
U2 - 10.1109/ICDCS54860.2022.00100
DO - 10.1109/ICDCS54860.2022.00100
M3 - Conference contribution
AN - SCOPUS:85140917776
T3 - Proceedings - International Conference on Distributed Computing Systems
SP - 994
EP - 1004
BT - Proceedings - 2022 IEEE 42nd International Conference on Distributed Computing Systems, ICDCS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 42nd IEEE International Conference on Distributed Computing Systems, ICDCS 2022
Y2 - 10 July 2022 through 13 July 2022
ER -