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Energy-efficient QoE-driven Strategies forContext-aware RAT Selection

Bouali, Faouzi, Moessner, Klaus and Fitch, Michael (2020) Energy-efficient QoE-driven Strategies forContext-aware RAT Selection IEEE Transactions on Green Communications and Networking.

TGCN-TPS-19-0082.pdf - Accepted version Manuscript

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This paper formulates an optimization problem thatmaximizes an aggregate utility that captures the “in-context” suit-ability of available radio access technologies (RATs) to supportadaptive video streaming subject to a single-homing constraint.To efficiently solve the considered problem, a novel network-assisted quality-of-experience (QoE)-driven methodology is de-vised, and its impact on the end-user devices is evaluated.The proposed approach is evaluated and benchmarked againstits distributed and centralized counterparts from a cost-benefitperspective. The results reveal that the proposed strategy sig-nificantly outperforms its distributed counterpart, and performsdifferently with respect to its centralized counterpart dependingon the number of video clients. At low loads, it performs similarlywith much less control overhead. At high loads, the proposedstrategy scales up well, while the centralized approach getsoverwhelmed by an increasing uplink signaling. A practicalityanalysis of the proposed strategy for battery-powered devicesreveals that its gain in terms of uplink signaling outweighs its costin terms of processing load, which results in a drastic reduction ofthe consumed energy. Therefore, the proposed solution providesa win-win situation, where the video clients can sustain goodQoE levels at reduced energy consumption, while the networkcan accommodate more users with existing capacity.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Date : 3 January 2020
Funders : The European Commission - H2020-ICT-19-2019
Copyright Disclaimer : © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : James Marshall
Date Deposited : 29 Jan 2020 12:14
Last Modified : 07 Feb 2020 16:55

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