Depth-Regulated and Energy-Balanced Routing for UWSNs Using Chaotic Search and Rescue Optimization

Subject Areas : Multimedia Processing, Communications Systems, Intelligent Systems

Saif Kadhim Mutar ¹ , Azam Andalib ² , Hossein Azgomi ³ , Seyed Ali Sharifi ⁴

1 - 1MSc Student, Department of Electrical and Computer Engineering, Urmia University, Urmia, Iran
2 - Assistant Professor, Department of Computer Engineering, Ra.C., Islamic Azad University, Rasht, Iran
3 - Assistant Professor, Department of Computer Engineering, Ra.C., Islamic Azad University, Rasht, Iran
4 - Assistant Professor, Department of Computer Engineering, B.C., Islamic Azad University, Bonab, Iran

Received: 2025-04-06 Accepted : 2025-05-18 Published : 2025-06-22

Keywords: underwater wireless sensor networks, depth control, routing, Clustering, search and rescue optimization algorithm and multi-hop data transfer,

Abstract :

Underwater wireless sensor networks (UWSNs) employ numerous inexpensive sensor nodes deployed in deep ocean environments. These nodes, characterized by their limited transmission power, resources, and energy, serve various purposes including disaster management, underwater navigation, and environmental monitoring. In these networks it is very challenging to update their location or add new devices, and it is very important to enhance the energy performance and lifetime of the underwater wireless sensor network. Multi-hop communication can expand the range of communication in these networks and increase its connections. The use of clustering-based routing is effective for increasing energy efficiency in these networks, with the difference that, unlike conventional wireless sensor networks, they have limitations such as low bandwidth, extended persistence, underwater pressure, and higher error probability. An energy balance routing protocol with multi-hop data transmission based on search and rescue (EBMH_CSR) is proposed, which balances by adjusting the depth of less energy nodes and replacing them with more energy nodes, and by combining chaotic concepts in the search and rescue optimization algorithm and with Considering residual energy, distance and degree of sensor nodes, fitness function is calculated. Simulation results show that the EBMH_CSR algorithm has improved the packet delivery rate (PDR) in different number of nodes by 23.6 percent, the packet reception rate (NPR) in different number of loads by 26.7 percent, the energy consumption in different number of rounds by 31.2 percent, the end-to-end delay by 31.7 percent, and the network lifetime in different number of nodes by 36 percent compared to the compared algorithms.

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