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Syst."],"published-print":{"date-parts":[[2022,7,31]]},"abstract":"<jats:p>\n            Heterogeneous\n            <jats:bold>multi-processor system-on-chip (MPSoC)<\/jats:bold>\n            smartphones are required to offer increasing performance and user\n            <jats:bold>quality-of-experience (QoE)<\/jats:bold>\n            , despite comparatively slow advances in battery technology. Approaches to balance instantaneous power consumption, performance and QoE have been reported, but little research has considered how to perform longer-term budgeting of resources across a complete battery discharge cycle. Approaches that have considered this are oblivious to the daily variability in the user\u2019s desired charging time-of-day (plug-in time), resulting in a failure to meet the user\u2019s battery life expectations, or else an unnecessarily over-constrained QoE. This paper proposes QUAREM, an adaptive resource management approach in mobile MPSoC platforms that maximises QoE while meeting battery life expectations. The proposed approach utilises a model that learns and then predicts the dynamics of the energy usage pattern and plug-in times. Unlike state-of-the-art approaches, we maximise the QoE through the adaptive balancing of the battery life and the\n            <jats:bold>quality of service (QoS)<\/jats:bold>\n            for the duration of the battery discharge. Our model achieves a good degree of accuracy with a mean absolute percentage error of 3.47% and 2.48% for the energy demand and plug-in times, respectively. Experimental evaluation on an off-the-shelf commercial smartphone shows that QUAREM achieves the expected battery life of the user within 20\u201325% energy demand variation with little or no QoE degradation.\n          <\/jats:p>","DOI":"10.1145\/3526116","type":"journal-article","created":{"date-parts":[[2022,3,21]],"date-time":"2022-03-21T12:37:55Z","timestamp":1647866275000},"page":"1-29","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["QUAREM: Maximising QoE Through Adaptive Resource Management in Mobile MPSoC Platforms"],"prefix":"10.1145","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2235-4091","authenticated-orcid":false,"given":"Samuel","family":"Isuwa","sequence":"first","affiliation":[{"name":"University of Southampton, Southampton, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6161-4637","authenticated-orcid":false,"given":"Somdip","family":"Dey","sequence":"additional","affiliation":[{"name":"University of Essex, Colchester, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andre P.","family":"Ortega","sequence":"additional","affiliation":[{"name":"Escuela Superior Polit\u00e9cnica del Litoral, Guayaquil, Ecuador"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2056-0569","authenticated-orcid":false,"given":"Amit Kumar","family":"Singh","sequence":"additional","affiliation":[{"name":"University of Essex, Colchester, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bashir M.","family":"Al-Hashimi","sequence":"additional","affiliation":[{"name":"Kings College London, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Geoff V.","family":"Merrett","sequence":"additional","affiliation":[{"name":"University of Southampton, Southampton, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,9,5]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.5555\/1870926.1870962"},{"key":"e_1_3_1_3_2","unstructured":"Apkpure.com. 2015. 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