BrezeFlow: Unified Debugger for Android CPU Power Governors and Schedulers on Edge Devices
Alexander Hoffman, Anuj Pathania, Philipp H. Kindt, Samarjit Chakraborty, Tulika Mitra
Abstract
Power management is quintessential to the successful deployment of edge devices, such as smartphones, in power-, thermal-, and energy-constrained environments. Governors and schedulers operate system sub-routines for power management at the edge. There exist several tools for debugging power issues in Android applications. However, there exists no tool to identify and classify inevitable misdecisions by power managers, given their often inefficient underlying heuristics. In this work, we introduce the first tool - BrezeFlow - designed for unified (scheduling and frequency scaling) power debugging of CPU power managers on Android edge devices. BrezeFlow enables kernel developers to evaluate designs of their power managers retrospectively with closed-source applications in real-world scenarios based on any user-defined strategy and thereby gain insights for better future governor designs. BrezeFlow detected an average of 815 misdecisions per second for the commonly deployed duo, ondemand governor and Completely Fair Scheduler, on mobile edge devices running popular applications.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext d3375b1a-23d8-4fc0-b178-c533d1f7c27aRelated papers
- CRAVE: Analyzing Cross-Resource Interaction to Improve Energy Efficiency in Systems-on-ChipDipayan Mukherjee, Sam Hachem, Jeremy Bao, Curtis Madsen et al.EuroSys 2025 · 2 citations
- EANeM: Energy-Aware Network Stack Management for Mobile DevicesChungseop Lee, Keonhyuk Lee, Mingoo Kang, Hyukjun LeeDAC 2020
- Lightweight Detection of Abnormal Battery Drain Induced by Network Operations of Mobile AppsRun Wang, Marco Brocanelli, Xiaorui WangINFOCOM 2026
- Balancing Energy Efficiency and Real-Time Performance in GPU SchedulingYidi Wang, Mohsen Karimi, Yecheng Xiang, Hyoseung KimRTSS 2021 · 29 citations
- NMAP: Power Management Based on Network Packet Processing Mode Transition for Latency-Critical WorkloadsKi-Dong Kang, Gyeongseo Park, Hyosang Kim, Mohammad Alian et al.MICRO 2021 · 18 citations
