ECM: Improving IoT Throughput with Energy-Aware Connection Management

Abstract

Designing Internet of Things (IoT) devices that solely rely on energy harvesting is the most promising approach towards achieving a scalable and sustainable IoT. The power output of energy harvesters can however vary significantly and maximizing throughput hence requires adapting application behavior to match the harvester's current power output. In this work, we focus on the connection policy of the IoT device and find that the on-demand connect policy -- which is used by state-of-the-art IoT runtime systems -- and the aggressive maintain connection policy both fall short across a broad range of harvester power outputs. We therefore propose Energy-aware Connection Management (ECM) which tunes the connection policy and sampling frequency to consistently achieve high throughput. ECM accomplishes this by predicting both the average power output of the harvester and the energy consumed by the IoT device with a lightweight analytical model that only requires tracking six energy thresholds. Our evaluation demonstrates that ECM can improve throughput substantially, i.e., by up to 9.5X and 3.0X compared to the on-demand connect and maintain connection policies, respectively.

ECM: Improving IoT Throughput with Energy-Aware Connection Management