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Title Depth Based Fog Assisted Data Collection Scheme For Time-Critical IOUT Applications

Author(s) Bushra Mehmood

Abstract The Internet of Underwater Things (IoUT) has emerged as a game-changer for underwater applications, with acoustic waves as its go-to communication medium. On the surface, radio signals dominate communication between sinks and onshore control centers. The fusion of IoUT with Fog Computing offers a robust platform for dynamic applications, from pipeline management to large-scale emergency responses and underwater infrastructure monitoring. Sink node delays in IoUT are primarily due to limited processing power, especially concerning routing protocols. Furthermore, redundant packet transmission, while forwarding data, not only escalates energy use but also introduces delays. The developed scheme is called Depth-based Fog Assisted Data Collection (DFDC) scheme for time-critical Internet of Underwater Things (IoUT) applications. DFDC leverages fog computing to ease the load on sink nodes, slashing packet delays to onshore control systems. Moreover, it deploys a strategy to curb redundant transmissions, enhancing latency and energy efficiency in the data forwarding process for ordinary underwater sensor nodes. DFDC is compared with a High-Availability Data Collection Scheme based on Multi-AUVs for Underwater Sensor Networks(HAMA) and Data Gathering algorithm for Sensors (DGS). Through extensive simulations and analysis, this research demonstrates that the DFDC protocol outperforms both HAMA and DGS in terms of reducing packet delivering ratio, conserving energy, and minimizing redundant data transmission. These findings underscore the potential of DFDC as a groundbreaking solution for improving underwater communication, promising more efficient and reliable data transmission in underwater scenarios. This study contributes valuable insights that can shape the future of underwater communication protocols.

Type Thesis/Dissertation MS

Faculty Engineering and Computer Science

Department Computer Science

Language English

Publication Date 2023-12-18

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