Energy-Efficient Clustering Algorithm Analysis for Intelligent Marine Ecosystem Monitoring

Marine ecosystems are complex and dynamic environments. Monitoring these ecosystems is essential for understanding and identifying potential threats and conservation needs. Different sensory devices such as wireless sensor networks (WSNs) are used to monitor these environments. WSN have been in industrial use for the last two decades. However, energy efficiency in WSNs remains a topic that requires attention. With the rise of artificial intelligence and machine learning, numerous techniques have been proposed for developing energy-efficient clustering algorithms. These algorithms aim to improve the efficiency of battery- driven sensors to prolong the network's lifetime by balancing the energy consumption among all nodes in the network. In this paper, we present a comprehensive evaluation and literature review of state-of-the-art energy-efficient clustering algorithms that can be used for intelligent marine ecosystem monitoring. The review aims to dive into the theoretical aspects of clustering in sensor networks and its application to energy optimization, offering insights into the various clustering schemes proposed for wireless sensors, specifically focusing on energy efficiency.