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- W3196996843 abstract "Mobile networks equipped with edge computing nodes enable access to information that can be leveraged to assist client-based adaptive bitrate (ABR) algorithms in making better adaptation decisions to improve both Quality of Experience (QoE) and fairness. For this purpose, we propose a novel on-the-fly edge mechanism, named EADAS (Edge Assisted Adaptation Scheme for HTTP Adaptive Streaming), located at the edge node that assists and improves the ABR decisions on-the-fly. EADAS proposes (i) an edge ABR algorithm to improve QoE and fairness for clients and (ii) a segment prefetching scheme. The results show a QoE increase of 4.6%, 23.5%, and 24.4% and a fairness increase of 11%, 3.4%, and 5.8% when using a buffer-based, a throughput-based, and a hybrid ABR algorithm, respectively, at the client compared with client-based algorithms without EADAS. Moreover, QoE and fairness among clients can be prioritized using parameters of the EADAS algorithm according to service providers’ requirements." @default.
- W3196996843 created "2021-09-13" @default.
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- W3196996843 date "2021-10-04" @default.
- W3196996843 modified "2023-09-25" @default.
- W3196996843 title "EADAS: Edge Assisted Adaptation Scheme for HTTP Adaptive Streaming" @default.
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- W3196996843 doi "https://doi.org/10.1109/lcn52139.2021.9524883" @default.
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