A Procedural Method to Predictively Assess Power-Quality Trade-Offs of Circuit-Level Adaptivity in IoT Systems - De Roose, Jaro; Andraud, Martin; Verhelst, Marian (Frontiers in Electronics, 2022)
The constant miniaturization of IoT sensor nodes requires a continuous reduction in battery sizes, leading to more stringent needs in terms of low-power operation. Over the past decades, an extremely large variety of techniques have been introduced to enable such reductions in power consumption. Many involve some form of Offline Reconfigurability (OfC), i.e. the ability to configure the node before deployment, or Online Adaptivity (OnA), i.e. the ability to also reconfigure the node during runtime. Yet, the inherent design trade-offs usually lead to ad-hoc OnA and OfC, which prevents assessing the varying benefits and costs each approach implies before investing in implementation on a specific node. To solve this issue, in this work we propose a generic predictive assessment methodology that enables to evaluate OfC and OnA globally, prior to any design. Practically, the methodology is based on optimization mathematics, to quickly and efficiently evaluate the potential benefits and costs from OnA relative to OfC. This generic methodology can thus determine which type of solution will consume the least amount of power, given a specific application scenario, before implementation. We apply the methodology on three adaptive IoT systems papers, to demonstrate the ability of the introduced methodology, bring insights into the adaptivity mechanics and quickly optimize the OfC-OnA adaptivity, even under scenarios with many adaptivity variables.