AERO: Adaptive and Efficient Runtime-Aware OTA Updates for Energy-Harvesting IoT

TL;DR

AERO introduces a runtime-aware OTA update system for energy-harvesting IoT devices that ensures consistency and efficiency despite intermittent energy availability by integrating updates into task scheduling.

Contribution

It presents a novel adaptive update mechanism that dynamically schedules updates within routine tasks considering energy constraints, improving reliability for intermittently powered IoT devices.

Findings

Enhanced update reliability over existing methods

Reduced overhead and reboot times

Effective adaptation to energy availability fluctuations

Abstract

Energy-harvesting (EH) Internet of Things (IoT) devices operate under intermittent energy availability, which disrupts task execution and makes energy-intensive over-the-air (OTA) updates particularly challenging. Conventional OTA update mechanisms rely on reboots and incur significant overhead, rendering them unsuitable for intermittently powered systems. Recent live OTA update techniques reduce reboot overhead but still lack mechanisms to ensure consistency when updates interact with runtime execution. This paper presents AERO, an Adaptive and Efficient Runtime-Aware OTA update mechanism that integrates update tasks into the device's Directed Acyclic Graph (DAG) and schedules them alongside routine tasks under energy and timing constraints. By identifying update-affected execution regions and dynamically adjusting dependencies, AERO ensures consistent up date integration while adapting to intermittent energy availability. Experiments on representative workloads demonstrate improved update reliability and efficiency compared to existing live update approaches.