Rights statement: © ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in NOSSDAV '20: Proceedings of the 30th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video http://doi.acm.org/10.1145/3386290.3396932
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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Evaluation of CMAF in live streaming scenarios
AU - Lyko, T.
AU - Broadbent, M.
AU - Race, N.
AU - Nilsson, M.
AU - Farrow, P.
AU - Appleby, S.
N1 - © ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in NOSSDAV '20: Proceedings of the 30th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video http://doi.acm.org/10.1145/3386290.3396932
PY - 2020/6/10
Y1 - 2020/6/10
N2 - HTTP Adaptive Streaming (HAS) technologies such as MPEG DASH are now used extensively to deliver television services to large numbers of viewers. In HAS, the client requests segments of content using HTTP, with an ABR algorithm selecting the quality at which to request each segment to trade-off video quality with the avoidance of stalling. This introduces significant end to end latency compared to traditional broadcast, due to the the client requiring a large enough buffer for the ABR algorithm to react to changes in network conditions in a timely manner. The recently standardised Common Media Application Format (CMAF) has helped address the issue of latency by defining segments as composed of independently transferable chunks. In this paper, we describe a simulation model we have developed to evaluate the performance of four popular ABR algorithms using DASH and CMAF in various low latency live streaming scenarios. Realistic network conditions are used for the evaluation, which are based on throughput data taken from the CDN logs of a commercial live TV service. We quantify the performance of the ABR algorithms using a selection of QoE metrics, and show that CMAF can significantly improve ABR performance in low delay scenarios.
AB - HTTP Adaptive Streaming (HAS) technologies such as MPEG DASH are now used extensively to deliver television services to large numbers of viewers. In HAS, the client requests segments of content using HTTP, with an ABR algorithm selecting the quality at which to request each segment to trade-off video quality with the avoidance of stalling. This introduces significant end to end latency compared to traditional broadcast, due to the the client requiring a large enough buffer for the ABR algorithm to react to changes in network conditions in a timely manner. The recently standardised Common Media Application Format (CMAF) has helped address the issue of latency by defining segments as composed of independently transferable chunks. In this paper, we describe a simulation model we have developed to evaluate the performance of four popular ABR algorithms using DASH and CMAF in various low latency live streaming scenarios. Realistic network conditions are used for the evaluation, which are based on throughput data taken from the CDN logs of a commercial live TV service. We quantify the performance of the ABR algorithms using a selection of QoE metrics, and show that CMAF can significantly improve ABR performance in low delay scenarios.
KW - ABR
KW - Adaptive streaming
KW - CMAF
KW - DASH
KW - Latency
KW - Live
KW - Video streaming
KW - Audio systems
KW - Computer graphics
KW - Economic and social effects
KW - HTTP
KW - Quality of service
KW - Client request
KW - End to end latencies
KW - Live streaming
KW - Media application
KW - Network condition
KW - Simulation model
KW - Video quality
KW - Motion Picture Experts Group standards
U2 - 10.1145/3386290.3396932
DO - 10.1145/3386290.3396932
M3 - Conference contribution/Paper
SP - 21
EP - 26
BT - NOSSDAV '20: Proceedings of the 30th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video
PB - ACM
CY - New York
ER -