DEPTH BASED FOG ASSISTED DATA COLLECTION SCHEME FOR TIME- CRITICAL IOUT APPLICATIONS

Abstract

The Internet of Underwater Things (IoUT) primarily relies on acoustic wave communication underwater, while radio signals are utilized at the surface. Integrating IoUT with Fog Computing significantly boosts the performance of applications such as underwater surveillance and pipeline inspection. However, challenges like processing delays at sink nodes due to limited computational capabilities, and energy inefficiencies caused by redundant data transmissions, still persist. To address these challenges, the DFDC protocol employs fog computing to optimize data flow, thereby reducing latency and eliminating unnecessary transmissions. When evaluated against existing methods such as the High-Availability Data Collection Scheme (HAMA) and the Data Gathering algorithm for Sensors (DGS), DFDC demonstrates superior performance by lowering packet delivery ratios, conserving energy, and minimizing duplicate data transfers.