Timely Communications for Remote Inference

arXiv:2404.16281v1 Announce Type: cross
Abstract: In this paper, we analyze the impact of data freshness on remote inference systems, where a pre-trained neural network infers a time-varying target (e.g., the locations of vehicles and pedestrians) based on features (e.g., video frames) observed at a sensing node (e.g., a camera). One might expect that the performance of a remote inference system degrades monotonically as the feature becomes stale. Using an information-theoretic analysis, we show that this is true if the feature …

abstract analyze arxiv communications cs.it cs.lg cs.ni data expect features impact inference locations math.it network neural network node paper pedestrians performance sensing systems type vehicles video