CAPMAN: Cooling and Active Power Management in big.LITTLE Battery Supported Devices

摘要

Modern smartphone is far from being ubiquitous due to limited energy capacity. Recent research suggests that heterogeneous batteries may expose power saving opportunities that fit dynamic software patterns. Yet it is still a challenge on thermal and power management for a hybrid battery pack in a smartphone. To address this challenge, we propose a system framework, called CAPMAN , which supports joint optimization of cooling and active power management in smartphones. The framework consists of three major techniques: 1) A Markov decision process (MDP) technique that models battery types, and cooling/active power use from state and action nodes; 2) A structural similarity approximation that speeds up the convergence of MDP computation, providing battery scheduling decisions; 3) A TEC and battery management facility to realize the cooling and active power management. In addition, CAPMAN provides an online algorithm with a proved worst-case ${mathbf{O}}left( {rac{1}{{1 - ho }}} ight)$-competitiveness performance, where ρ is the factor of discount. We have prototyped CAPMAN with popular smartphones and heterogeneous batteries, and evaluated them with real-world workloads. Results show that CAPMAN can achieve 114% longer service time under skewed loads, compared to the original phone. Compared to the state-of-the-practice baselines, CAPMAN shows 55% performance gain and 53% less energy use on average. As such, CAPMAN approves that big.LITTLE batteries with a careful system design is an effective way to prolong smartphone service times.