A1 Journal article – refereed

UBAR: User- and Battery-aware Resource Management for Smartphones




List of Authors: Shamsa Elham, Pröbstl Alma, TaheriNejad Nima, Kanduri Anil, Chakraborty Samarjit, Rahmani Amir M., Liljeberg Pasi

Publisher: ASSOC COMPUTING MACHINERY

Publication year: 2021

Journal: ACM Transactions in Embedded Computing Systems

Journal acronym: ACM T EMBED COMPUT S

Volume number: 20

Issue number: 3

Number of pages: 25

ISSN: 1539-9087

eISSN: 1558-3465

DOI: http://dx.doi.org/10.1145/3441644


Abstract
Smartphone users require high Battery Cycle Life (BCL) and high Quality of Experience (QoE) during their usage. These two objectives can be conflicting based on the user preference at run-time. Finding the best trade-off between QoE and BCL requires an intelligent resource management approach that considers and learns user preference at run-time. Current approaches focus on one of these two objectives and neglect the other, limiting their efficiency in meeting users' needs. In this article, we present UBAR, User- and Battery-aware Resource management, which considers dynamic workload, user preference, and user plug-in/out pattern at run-time to provide a suitable trade-off between BCL and QoE. UBAR personalizes this trade-off by learning the user's habits and using that to satisfy QoE, while considering battery temperature and State of Charge (SOC) pattern to maximize BCL. The evaluation results show that UBAR achieves 10% to 40% improvement compared to the existing state-of-the-art approaches.


Last updated on 2021-04-11 at 13:49