This paper analyzes models for parallel processing of signals from Internet of Things (IoT) sensors in a fog computing environment. The limited resources of sensor nodes are a major challenge in ensuring processing efficiency for real-time applications. The paper reviews three main parallel processing models: multi-core chip systems, hierarchical signal processing, and distributed adaptive filtering, along with their architecture, advantages, and application areas. It also discusses the possibilities of reducing latency in fog networks through the deployment of service function trees and horizontal task distribution mechanisms.
Models for Parallel Processing of Signals Received from IOT Sensors in Foggy Networks
DOI:
Keywords:
IoT
fog computing
parallel processing
Abstract
References
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