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The optimization of nodes clustering and multi-hop routing protocol using hierarchical chimp optimization for sustainable energy efficient underwater wireless sensor networks

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Abstract

The design of underwater wireless sensor networks (UWSNs) faces many challenges, including power consumption, storage, battery life, and transmission bandwidth. UWSNs usually either use node clustering or multi-hop routing as their energy-efficient optimization algorithms. The cluster optimization technique will organize the sensor nodes into a cluster network, with each cluster led by a cluster head (CH). In contrast, the multi-hop optimization algorithm will create a multi-hop network by sending data to the base station (BS) while switching between different sensor nodes. However, the overburdens of CH nodes impact the performance of the cluster optimization method, whereas the overburdens of nodes close to the BS impact the performance of the multi-hop optimization algorithm. Therefore, clustering and routing procedures can be considered as a simultaneous NP-hard problem that metaheuristic algorithms can address. With this motivation, this paper proposes an energy-efficient clustering and multi-hop routing protocol using the metaheuristic-based algorithm to increase energy efficiency in UWSNs and lengthen the network life. However, the existing metaheuristic-based methods use two separate algorithms for clustering and multi-hop routing, increasing computational complexity, different initialization, and difficulty in hyperparameters’ tuning. In order to address the mentioned shortcomings, this paper proposes a novel hierarchical structure called hierarchical chimp optimization (HChOA) for both clustering and multi-hop routing processes. The proposed HChOA is validated using various metrics after being simulated using an extended set of experiments. Results are compared to those from LEACH, TEEN, MPSO, PSO, and IPSO-GWO to validate the impact of the HChOA. According to the findings, the HChOA performed better than other lifespan and energy usage benchmarks.

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Authors and Affiliations

  1. School of Artificial Intelligence, Chongqing Creation Vocational College, Yongchuan, Chongqing, 402160, China

    Shukun He

  2. Faculty of Engineering, Chengdu College of University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, China

    Qinlin Li

  3. Department of Electrical and Electronics Engineering, Faculty of Engineering, Technology and Built Environment, UCSI University, Cheras, 56000, Kuala Lumpur, Malaysia

    Qinlin Li

  4. Department of Electrical Engineering, Imam Khomeini Marine Science University, Nowshahr, Iran

    Mohammad Khishe & Hassan Mohammadi

  5. Department of Software and Informatics Engineering, College of Engineering, Salahaddin University, Erbil, Kurdistan Region, Iran

    Amin Salih Mohammed

  6. Department of Computer Engineering, College of Engineering and Computer Science, Lebanese French University, Erbil, Kurdistan Region, Iraq

    Amin Salih Mohammed

  7. Department of Information Technology, College of Engineering and Computer Science, Lebanese French University, Erbil, Kurdistan Region, Iraq

    Mokhtar Mohammadi

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  1. Shukun He
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He, S., Li, Q., Khishe, M. et al. The optimization of nodes clustering and multi-hop routing protocol using hierarchical chimp optimization for sustainable energy efficient underwater wireless sensor networks. Wireless Netw 30, 233–252 (2024). https://doi.org/10.1007/s11276-023-03464-9

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  • DOI: https://doi.org/10.1007/s11276-023-03464-9

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