Quantifying the variability of power and energy consumption for IoT edge nodes

Abstract

For IoT and edge systems, measuring, predicting and optimizing energy consumption is an open field. It is important to accurately and precisely characterize power and energy consumption of edge nodes, as energy can be a scarce and key resource. However, there are no fine-grain studies that aim at understanding the potential variability of power and energy consumption of edge nodes. Existing research works give minor or no significance to this potential variability. This paper addresses this problem by quantifying the variability of power and energy consumption on a single edge node, and among multiple homogeneous edge nodes, for three scenarios: Idle, CPU intensive “matrix product” and RAM intensive “flip”. These scenarios are found in edge applications. Identical controlled experiments are repeated thoroughly, for each scenario. Results show that power and energy variability exist for all studied scenarios. On a single node, power and energy variability measurements are relatively low. On multiple homogeneous nodes, the variability can be significant. For example, for CPU intensive “matrix product”, the variability in energy is equivalent to an idle up-time, in a month, of 7 hours and 52 hours, when considering single and multiple homogeneous nodes, respectively.