Abstract:
We propose a kernel-level energy profiling tool KLEP that can work with diverse APIs of Android. KLEP addresses the challenges of the tail energy problem and the complex ...Show MoreMetadata
Abstract:
We propose a kernel-level energy profiling tool KLEP that can work with diverse APIs of Android. KLEP addresses the challenges of the tail energy problem and the complex interrelation between hardware components in the device energy consumption profile. KLEP collects energy-sensitive events in the kernel and measures real energy consumption of the device at the same time, and employs a LSTM neural-network-based model for energy profiling. The preliminary results show that the curves profiled by KLEP can match the actual energy consumption with low error and overhead.
Published in: 2017 16th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)
Date of Conference: 18-21 April 2017
Date Added to IEEE Xplore: 12 June 2017
ISBN Information:
Conference Location: Pittsburgh, PA, USA