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• W4293102306 abstract "Heterogeneous multi-processor system-on-chip (MPSoC) smartphones are required to offer increasing performance and user quality-of-experience (QoE) , 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’s desired charging time-of-day (plug-in time), resulting in a failure to meet the user’s 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 quality of service (QoS) 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 20–25% energy demand variation with little or no QoE degradation." @default.
• W4293102306 created "2022-08-26" @default.
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• W4293102306 date "2022-07-31" @default.
• W4293102306 modified "2023-09-29" @default.
• W4293102306 title "QUAREM: Maximising QoE Through Adaptive Resource Management in Mobile MPSoC Platforms" @default.
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• W4293102306 doi "https://doi.org/10.1145/3526116" @default.
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