Selective Task offloading for Maximum Inference Accuracy and Energy efficient Real-Time IoT Sensing Systems

arXiv:2402.16904v1 Announce Type: new
Abstract: The recent advancements in small-size inference models facilitated AI deployment on the edge. However, the limited resource nature of edge devices poses new challenges especially for real-time applications. Deploying multiple inference models (or a single tunable model) varying in size and therefore accuracy and power consumption, in addition to an edge server inference model, can offer a dynamic system in which the allocation of inference models to inference jobs is performed according to the current …

abstract accuracy ai deployment applications arxiv challenges cs.ai cs.lg deployment devices edge edge devices energy energy efficient inference iot multiple nature real-time real-time applications sensing small systems the edge type