Exploring Offloading Strategies in the Analysis of Vital Signs in Fog Computing

This paper proposes the Decentralized Adaptive Priority-based Hierarchical Offloading (DAPHO) model for offloading strategies in fog computing applied to healthcare in smart cities. The model handles large volumes of IoT data by prioritizing critical signals in the fog while less critical ones are processed in the cloud. Unlike centralized or single-path approaches, DAPHO enables autonomous offloading decisions among fog nodes hierarchically organized (e.g., neighborhoods, cities). The flexibility of multiple destinations and dynamic thresholds improved response time and prioritized signal processing, although fixed thresholds showed better performance in some scenarios