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.

中文翻译：

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乌巴

智能手机用户在使用过程中需要高电池循环寿命 (BCL) 和高体验质量 (QoE)。根据运行时的用户偏好，这两个目标可能会发生冲突。在 QoE 和 BCL 之间找到最佳权衡需要一种智能的资源管理方法，该方法在运行时考虑并了解用户偏好。当前的方法侧重于这两个目标之一而忽略了另一个，从而限制了它们在满足用户需求方面的效率。在本文中，我们介绍了 UBAR（用户感知和电池感知资源管理），它在运行时考虑动态工作负载、用户偏好和用户插入/退出模式，以在 BCL 和 QoE 之间提供合适的权衡。UBAR 通过了解用户的习惯并使用它来满足 QoE 来个性化这种权衡，同时考虑电池温度和充电状态 (SOC) 模式以最大化 BCL。评估结果表明，与现有的最先进方法相比，UBAR 实现了 10% 到 40% 的改进。