Synergy Optimized Routing Protocol for Multiobjective Optimization in Underwater Communication Networks

被引:0
作者
Saleem, Kiran [1 ]
Wang, Lei [1 ]
Ahmed, Rana Zeeshan [2 ]
Almadhor, Ahmad [3 ]
Srivastava, Gautam [4 ,5 ,6 ]
Gadekallu, Thippa Reddy [6 ,7 ,8 ]
机构
[1] Dalian Univ Technol, Sch Software, Dalian 30332, Peoples R China
[2] Univ Sialkot, Dept Informat Technol, Sialkot 51040, Pakistan
[3] Jouf Univ, Coll Comp & Informat Sci, Dept Comp Engn & Networks, Sakaka 72388, Saudi Arabia
[4] Brandon Univ, Dept Math & Comp Sci, Brandon, MB R7A 6A9, Canada
[5] China Med Univ, Res Ctr Interneural Comp, Taichung 404, Taiwan
[6] Chitkara Univ, Inst Engn & Technol, Ctr Res Impact & Outcome, Rajpura 140401, India
[7] Zhejiang A&F Univ, Coll Math & Comp Sci, Hangzhou 311300, Peoples R China
[8] Lovely Profess Univ, Div Res & Dev, Phagwara 144411, India
来源
IEEE INTERNET OF THINGS JOURNAL | 2025年 / 12卷 / 06期
关键词
Routing; Routing protocols; Optimization; Energy efficiency; Energy consumption; Data communication; Underwater communication; Real-time systems; Internet of Things; Wireless sensor networks; Artificial intelligence; fuzzy logics; intelligent reasoning; Internet of Underwater Things (IoUT); multiagent-system; synergy optimization; underwater communication networks; WIRELESS SENSOR NETWORKS;
D O I
10.1109/JIOT.2024.3496298
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Underwater communication systems face challenges, including limited bandwidth, high latency, and void areas. This article introduces synergy optimization routing protocol (SORP) for Internet of Underwater (IoU) sensor networks, emphasizing link scheduling to address localization, energy consumption, latency, network longevity, and void regions. Leveraging belief-desire-intention (BDI) and fuzzy logic, SORP offers adaptive responses to varying network conditions. Theoretical modeling using NetLogo enhances the understanding of SORP's behavior. In evaluation, SORP consistently outperforms others. Demonstrating superior energy efficiency (3.0-3.9) compared to PPWURC, state prediction-based data collection (SPDC), balanced routing protocol based on machine learning (BRP-ML) (40-120), and energy efficient clustering routing protocol based on arithmetic progression (5-6.5), SORP proves its efficacy. Latency analysis reveals SORP consistently displaying the lowest values (2.0-2.8), surpassing packet hierarchy and void processing, SPDC, and BRP-ML (8.3-30.0). With a perfect packet delivery ratio (PDR) of 98%, SORP showcases exceptional reliability. Network lifetime analysis positions SORP as a durable option, lasting from 3985 to 4010 rounds. Validation through an underwater communication system demonstrates speeds of 5 Mb/s and above. Simulation testing reveals a transmission speed of 80 bps with latency of less than 4 s and 98% PDR. Theoretical predictions indicate significant improvements in real-time transmission, reducing latency to less than 1 s with a speed of 5 Mb/s. This research presents an innovative and practical approach to address underwater communication challenges, highlighting the efficiency and reliability of SORP in routing protocols for underwater sensor networks. The combination of theoretical modeling and real-time testing offers a comprehensive understanding, emphasizing the potential real-world impact of SORP.
引用
收藏
页码:7306 / 7319
页数:14
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