Open Access

ARTICLE

Fuzzy Decision-Based Clustering for Efficient Data Aggregation in Mobile UWSNs

Aadil Mushtaq Pandith¹, Manni Kumar², Naveen Kumar³, Nitin Goyal^4,*, Sachin Ahuja², Yonis Gulzar⁵, Rashi Rastogi⁶, Rupesh Gupta⁷

1 Department of Computer Science and Engineering, Lovely Professional University, Jalandhar, 144402, Punjab, India
2 Department of Computer Science and Engineering, Chandigarh University, Mohali, 140413, Punjab, India
3 Salesforce Inc., Dallas, TX 75201, USA
4 Department of Computer Science and Engineering, School of Engineering and Technology, Central University of Haryana, Mahendragarh, 123031, Haryana, India
5 Department of Management Information Systems, College of Business Administration, King Faisal University, Al-Ahsa, 31982, Saudi Arabia
6 Department of Computer Application, Sir Chhotu Ram Institute of Engineering and Technology, Ch. Charan Singh University, Meerut, 250001, Uttar Pradesh, India
7 Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, 140401, Punjab, India

* Corresponding Author: Nitin Goyal. Email:

Computers, Materials & Continua 2025, 83(1), 259-279. https://doi.org/10.32604/cmc.2025.062608

Received 23 December 2024; Accepted 19 February 2025; Issue published 26 March 2025

Abstract

Underwater wireless sensor networks (UWSNs) rely on data aggregation to streamline routing operations by merging information at intermediate nodes before transmitting it to the sink. However, many existing data aggregation techniques are designed exclusively for static networks and fail to reflect the dynamic nature of underwater environments. Additionally, conventional multi-hop data gathering techniques often lead to energy depletion problems near the sink, commonly known as the energy hole issue. Moreover, cluster-based aggregation methods face significant challenges such as cluster head (CH) failures and collisions within clusters that degrade overall network performance. To address these limitations, this paper introduces an innovative framework, the Cluster-based Data Aggregation using Fuzzy Decision Model (CDAFDM), tailored for mobile UWSNs. The proposed method has four main phases: clustering, CH selection, data aggregation, and re-clustering. During CH selection, a fuzzy decision model is utilized to ensure efficient cluster head selection based on parameters such as residual energy, distance to the sink, and data delivery likelihood, enhancing network stability and energy efficiency. In the aggregation phase, CHs transmit a single, consolidated set of non-redundant data to the base station (BS), thereby reducing data duplication and saving energy. To adapt to the changing network topology, the re-clustering phase periodically updates cluster formations and reselects CHs. Simulation results show that CDAFDM outperforms current protocols such as CAPTAIN (Collection Algorithm for underwater oPTical-AcoustIc sensor Networks), EDDG (Event-Driven Data Gathering), and DCBMEC (Data Collection Based on Mobile Edge Computing) with a packet delivery ratio increase of up to 4%, an energy consumption reduction of 18%, and a data collection latency reduction of 52%. These findings highlight the framework’s potential for reliable and energy-efficient data aggregation mobile UWSNs.

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Keywords

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