Energy-efficient unequal multi-level clustering for underwater wireless sensor networks

Abstract

Underwater Wireless Sensor Networks (UWSNs) have emerged as a critical piece of technology for a wide range of maritime applications, including environmental monitoring, resource exploration, and catastrophe avoidance. An Energy Efficient Unequal Multilevel Clustering (EEUMC) algorithm tailored to UWSNs is proposed in this study. The EEUMC's primary purpose is to enhance the efficiency of data movement inside the network while decreasing the amount of energy lost. The proposed method employs a multilevel clustering framework, which divides the network into hierarchical groups based on node attributes and residual energy content. EEUMC introduces an unequal clustering technique, which differs from traditional clustering approaches. Cluster heads (CHs) are dynamically selected in this technique based on their energy levels as well as their proximity to sink nodes. The EEUMC integrates sophisticated routing protocols and adaptive data aggregation techniques in order to boost the energy economy even further. The routing algorithms route data flows across energy-efficient channels automatically, and adaptive data aggregation reduces redundant transmissions to conserve energy and keep the system functioning smoothly. This particular configuration of unequal clustering, intelligent routing, and adaptive aggregation all work together to improve data-collecting efficiency and network’s lifespan. The efficiency of the proposed EEUMC scheme was thoroughly tested through a number of simulations and head-to-head comparisons with alternative clustering approaches. When compared to more traditional approaches, the findings reveal that EEUMC greatly increases network longevity and data transmission rates. Furthermore, the scheme is robust in the sense that it can withstand changing network conditions while still ensuring a balanced consumption of energy across all nodes.