Comparison of Under Water Wireless Communication Using Deep Learning


Authors : K. Sathiya Priya; K. Prasad; K.V. Ganesh Reddy; K. Yenosh Kumar; K. Arjun

Volume/Issue : Volume 9 - 2024, Issue 4 - April

Google Scholar : https://tinyurl.com/5n7kj5d5

Scribd : https://tinyurl.com/mvd4bhxy

DOI : https://doi.org/10.38124/ijisrt/IJISRT24APR899

Abstract : The challenges encountered in aquatic communication systems encompass colourful factors, including limited bandwidth, high energy consumption rates, extended propagation detention times, End- to- End Delay(E-ED), media access control, routing complications, resource application, and power constraints. These challenges bear the perpetration of energy-effective protocols, which can be distributed into localization- grounded or localization-free protocols. This design primarily focuses on reviewing and assaying localization-free protocols, considering environmental variables, data transmission rates, transmission effectiveness, energy consumption rates, E-ED, and propagation detainments. Through a comprehensive review, the design aims to identify the strengths and sins of being protocols, thereby paving the way for unborn advancements in Aquatic Wireless Sensor Networks (UWSNs). The proposed check entails an in- depth examination of localization-free protocols, pressing the specific problems addressed and the crucial parameters considered during routing in UWSNs. Unlike former checks, this study concentrates on the current state- of- the- art routing protocols, emphasizing the routing strategy issues they attack. By emphasizing the advantages of each protocol, the design seeks to decide energy-effective results. likewise, detailed descriptions of the routing strategies employed by each protocol are handed to enhance appreciation. also, the downsides of each protocol are strictly examined to grease farther disquisition and identify the most suitable protocol. The comprehensive analysis of routing strategies, along with the delineation of pros and cons, not only sheds light on being challenges but also offers precious perceptivity into unborn exploration directions. By presenting open challenges and delineating implicit exploration avenues, this design aims to contribute to the ongoing elaboration and enhancement of aquatic communication systems.

Keywords : Underwater Wireless Communication, Deep Learning, Prediction Models, Machine Learning, Neural Networks, Communication Performance, Signal Propagation, Underwater Environment.

The challenges encountered in aquatic communication systems encompass colourful factors, including limited bandwidth, high energy consumption rates, extended propagation detention times, End- to- End Delay(E-ED), media access control, routing complications, resource application, and power constraints. These challenges bear the perpetration of energy-effective protocols, which can be distributed into localization- grounded or localization-free protocols. This design primarily focuses on reviewing and assaying localization-free protocols, considering environmental variables, data transmission rates, transmission effectiveness, energy consumption rates, E-ED, and propagation detainments. Through a comprehensive review, the design aims to identify the strengths and sins of being protocols, thereby paving the way for unborn advancements in Aquatic Wireless Sensor Networks (UWSNs). The proposed check entails an in- depth examination of localization-free protocols, pressing the specific problems addressed and the crucial parameters considered during routing in UWSNs. Unlike former checks, this study concentrates on the current state- of- the- art routing protocols, emphasizing the routing strategy issues they attack. By emphasizing the advantages of each protocol, the design seeks to decide energy-effective results. likewise, detailed descriptions of the routing strategies employed by each protocol are handed to enhance appreciation. also, the downsides of each protocol are strictly examined to grease farther disquisition and identify the most suitable protocol. The comprehensive analysis of routing strategies, along with the delineation of pros and cons, not only sheds light on being challenges but also offers precious perceptivity into unborn exploration directions. By presenting open challenges and delineating implicit exploration avenues, this design aims to contribute to the ongoing elaboration and enhancement of aquatic communication systems.

Keywords : Underwater Wireless Communication, Deep Learning, Prediction Models, Machine Learning, Neural Networks, Communication Performance, Signal Propagation, Underwater Environment.

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