QUAREM: Maximising QoE Through Adaptive Resource Management in Mobile MPSoC Platforms

Samuel Isuwa, Somdip Dey, Andre P. Ortega, Amit Kumar Singh, Bashir M. Al-Hashimi, Geoff V. Merrett

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

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.

Original languageEnglish
Article number38
JournalACM Transactions on Embedded Computing Systems
Volume21
Issue number4
DOIs
Publication statusPublished - 5 Sept 2022

Keywords

  • adaptive resource management
  • Battery budgeting
  • heterogeneous MPSoC
  • maximising user experience
  • QoE-aware resource management
  • quality of experience

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