WSN and Fog Computing Integration for Intelligent Data Processing

TL;DR

This paper explores integrating Wireless Sensor Networks with fog computing to enhance data processing efficiency in IoT systems, proposing a three-layer topology for improved smart data monitoring.

Contribution

It introduces a hierarchical fog computing approach with a three-layer topology to optimize data processing in IoT sensor networks.

Findings

Reduced communication and computational effort through hierarchical processing

Improved information-to-noise ratio in data monitoring

Effective deployment in unstructured environments

Abstract

Networked embedded systems endowed with sensing, computing, control and communication capabilities allow the development of various application scenarios and represent the building blocks of the Internet of Things (IoT) paradigm. Traditional data collection methods include multiple field level IoT systems that can relay data stemming from a network of distributed ground sensors directly to a cloud platform for storage, analysis and processing. In such applications however, rapid sensor deployment in unstructured environments represents a challenge to the overall robustness of the system. We discuss the fog and mist computing approaches to hierarchically process data along its path from source to destination. The several stages of intermediate data processing reduce the computational and communication effort in a gradual manner. A three-layer topology for smart data monitoring and processing is thus proposed and illustrated to improve the information to noise ratio in a reference scenario.