CROSS-LAYER LATENCY IN BLOCKCHAIN-ENABLED HIOT: A COMPREHENSIVE SURVEY
TL;DR
This study reviews latency-reduction approaches across the data filtering and encryption layers using a micro–macro perspective, and proposes a dependency-aware model that links local processing with propagation, queueing, consensus and storage.
Abstract
The Healthcare Internet of Things (HIoT) supports real-time monitoring and clinical decision-making through interconnected medical devices and sensors. Fog computing reduces communication delay by processing data near its source, while blockchain improves security, integrity, and decentralized trust. However, filtering, encryption, authentication, queueing, and consensus introduce additional latency, particularly in resource-constrained HIoT environments. Existing studies mainly address system-level delay, while micro-latency from local processing, hashing, memory access, and verification remains comparatively less explored. This study reviews latency-reduction approaches across the data filtering and encryption layers using a micro–macro perspective. A dependency-aware model links local processing with propagation, queueing, consensus and storage. Reported results are interpreted according to their architectural and evaluation conditions, while component-level analysis distinguishes isolated effects from coupled architectural improvements, showing that end-to-end latency arises from interactions across multiple processing stages.