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A cache-level quality of experience metric to characterize ICNs for adaptive streaming

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Li_2018_IEEECL_Cache_level_AAM.pdf (462.0Kb)
Date
02/2019
Author
Li, Wenjie
Fayed, Marwan
Oteafy, Sharief M. A.
Hassanein, Hossam S.
Keywords
Dynamic Adaptive Streaming
In-network caching
Performance metrics
QA75 Electronic computers. Computer science
T Technology
NDAS
BDC
R2C
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Abstract
Adaptive streaming has motivated information-centric network (ICN) designs to improve end-user quality of experience (QoE). However, their management and evaluation rely either on conventional cache-level metrics that are poor representations of QoE, or consumer-side indicators that are opaque to network services. This letter proposes a measure to bridge the gap between cache performance and consumer QoE. We introduce maximal sustainable bitrate (MSB), defined as the highest bitrate deliverable in time to be in time to meet a given request without buffering. Based on our observations, we posit that QoE is maximal when requested bitrates match a cache’s MSB for that content. We design a cache-level reward function as a benchmark metric that measures the difference between requested bitrates and MSB. We hypothesize that aggregated rewards are an indicator of overall system performance. Performance evaluations show high correlation between the sum of cache rewards and consumer QoE.
Citation
Li , W , Fayed , M , Oteafy , S M A & Hassanein , H S 2019 , ' A cache-level quality of experience metric to characterize ICNs for adaptive streaming ' , IEEE Communications Letters , vol. 23 , no. 2 , 8594670 , pp. 262-265 . https://doi.org/10.1109/LCOMM.2018.2890223
Publication
IEEE Communications Letters
Status
Peer reviewed
DOI
https://doi.org/10.1109/LCOMM.2018.2890223
ISSN
1089-7798
Type
Journal article
Rights
© 2018, IEEE. This work has been made available online in accordance with the publisher's policies. This is the author created accepted version manuscript following peer review and as such may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1109/LCOMM.2018.2890223
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/16897

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