Profiling and Improving the Duty-Cycling Performance of Linux-based IoT Devices

TL;DR

This paper investigates and enhances duty-cycling in Linux-based IoT devices, reducing energy consumption by optimizing boot/shutdown processes and introducing 'Pallex' for concurrent application execution, leading to significant lifetime improvements.

Contribution

It introduces 'Pallex', a parallel execution framework, and provides detailed analysis and improvements for duty-cycling performance on Raspberry Pi devices, including process optimization and impact of SD card factors.

Findings

System lifetime increased by up to 30.2% with Pallex.

Optimized process management reduces boot time and energy use.

SD card speed and capacity influence boot duration and energy consumption.

Abstract

Minimizing the energy consumption of Linux-based devices is an essential step towards their wide deployment in various IoT scenarios. Energy saving methods such as duty-cycling aim to address this constraint by limiting the amount of time the device is powered on. In this work we study and improve the amount of time a Linux-based IoT device is powered on to accomplish its tasks. We analyze the processes of system boot up and shutdown on two platforms, the Raspberry Pi 3 and Raspberry Pi Zero Wireless, and enhance duty-cycling performance by identifying and disabling time-consuming or unnecessary units initialized in the userspace. We also study whether SD card speed and SD card capacity utilization affect boot up duration and energy consumption. In addition, we propose 'Pallex', a parallel execution framework built on top of the 'systemd init' system to run a user application concurrently with userspace initialization. We validate the performance impact of Pallex when applied to various IoT application scenarios: (i) capturing an image, (ii) capturing and encrypting an image, (iii) capturing and classifying an image using the the k-nearest neighbor algorithm, and (iv) capturing images and sending them to a cloud server. Our results show that system lifetime is increased by 18.3%, 16.8%, 13.9% and 30.2%, for these application scenarios, respectively.