O/S Level Interrupt Prediction for Performance and Energy Management on Android

Abstract

Billions smartphones and smart objects battery-powered use Android, i.e. on the Linux kernel. To save energy, the main kernel leverage is to put processors in a low power state as soon as they are idle. It predicts the next event to estimate the sleep duration and choose a sleep state accordingly. Several wake-up sources (interrupts, events...) impact this prediction which is usually done considering them as a single source. The resulting signal is nearly random and difficult to predict. Processors are recently supporting deeper idle states but the prediction paradigm was never challenged. We propose to predict the next event by splitting the wake-up source signal into simpler event patterns. We describe a fast and efficient algorithm and its kernel-level performance evaluation. We compare our approach with multiple reference sleep state selection algorithms on actual ARM and x86 boards using classical mobile workloads. Our proposal detects correctly (up to 20% improved correctness leading to 5% reduced energy consumption) the time of next interrupt, and thus the right sleep level for the processor. We show and discuss the energy impact of the tested prediction algorithm and we compare it with the different generations of sleep level managers in the Linux kernel.