A Hierarchical Framework for Distributed Inference at the Edge

Abstract

To maximize AI potential in distributed environments, managing shared resources is vital for ensuring equitable user access. This poster presents the Hierarchical Inference Framework (HIF), a decentralized mechanism that optimizes collective performance across edge devices without explicit intercommunication. Key Challenge: Preventing network saturation and the dominance of high-power nodes to ensure fairness across heterogeneous devices