TY - GEN
T1 - Adaptive Video Transmission Strategy Based on Ising Machine
AU - Wei, Bo
AU - Song, Hang
AU - Katto, Jiro
N1 - Funding Information:
This research is supported by the Fujitsu-Waseda Digital Annealer FWDA Research Project, JSPS KAKENHI Grant No. 20K14740, and Waseda University Grant for Special Research Projects (No. 2021C-132 and No. 2021E-013).
Publisher Copyright:
© 2021 Owner/Author.
PY - 2021/11/15
Y1 - 2021/11/15
N2 - With the dramatically increasing video streaming in the total network traffic, it is critical to develop effective algorithms to ensure the quality of content delivery service. Adaptive bitrate (ABR) control is the most essential technique which determines the proper bitrate to be chosen based on network conditions, thus realize high-quality video streaming. In this paper, a novel ABR strategy is proposed based on Ising machine by using the quadratic unconstrained binary optimization (QUBO) method and Digital Annealer (DA) for the first time. The proposed method is evaluated by simulation with the real-world measured throughput and compared with other state-of-the-art methods. Experiment results show that the proposed QUBO-based method can outperform the existing methods, which demonstrating the superior of the proposed QUBO-based method.
AB - With the dramatically increasing video streaming in the total network traffic, it is critical to develop effective algorithms to ensure the quality of content delivery service. Adaptive bitrate (ABR) control is the most essential technique which determines the proper bitrate to be chosen based on network conditions, thus realize high-quality video streaming. In this paper, a novel ABR strategy is proposed based on Ising machine by using the quadratic unconstrained binary optimization (QUBO) method and Digital Annealer (DA) for the first time. The proposed method is evaluated by simulation with the real-world measured throughput and compared with other state-of-the-art methods. Experiment results show that the proposed QUBO-based method can outperform the existing methods, which demonstrating the superior of the proposed QUBO-based method.
KW - Adaptive Bitrate Control
KW - DASH
KW - Digital Annealer
KW - Ising Machine
KW - QUBO
UR - http://www.scopus.com/inward/record.url?scp=85120868514&partnerID=8YFLogxK
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U2 - 10.1145/3485730.3492892
DO - 10.1145/3485730.3492892
M3 - Conference contribution
AN - SCOPUS:85120868514
T3 - SenSys 2021 - Proceedings of the 2021 19th ACM Conference on Embedded Networked Sensor Systems
SP - 397
EP - 398
BT - SenSys 2021 - Proceedings of the 2021 19th ACM Conference on Embedded Networked Sensor Systems
PB - Association for Computing Machinery, Inc
T2 - 19th ACM Conference on Embedded Networked Sensor Systems, SenSys 2021
Y2 - 15 November 2021 through 17 November 2021
ER -