Energy Consumption Optimization in Wireless Sensor Network (WSN) Using Clustering Algorithm for Precision Agriculture
Keywords:
Energy-Efficient Clustering Protocol, Precision Agriculture IoT-WSN, Metaheuristic Optimization Algorithm, Network Lifetime Prolongation, Optimal Cluster Head Selection, Sustainable Smart Farming InfrastructureAbstract
Energy constraints on sensor nodes pose a critical challenge in implementing Wireless Sensor Networks (WSNs) for precision agriculture, where battery replacement across large fields is often impractical from both a technical and economic perspective. This research aims to optimize energy consumption by developing a hybrid clustering algorithm specifically designed to mitigate workload imbalance among nodes. The proposed methodology, Optimized Clustering Agriculture (OCA), uses a multi-objective fitness function that combines residual energy, Euclidean distance to the Base Station, and neighbor density to select the optimal Cluster Head (CH).
This modeling is performed using a first-order radio model to measure energy dissipation during the data transmission and aggregation phases. The results show that the OCA algorithm significantly outperforms conventional protocols such as LEACH, with up to a 30% increase in network lifetime and a reduction in first node failures (FDD) up to the 2,450th round. Furthermore, the system maintains a Packet Delivery Ratio (PDR) above 96%, ensuring the reliability of sensor data for decision-making in smart agriculture. These findings provide theoretical contributions to energy-efficient network protocols as well as practical contributions to supporting sustainable and energy-independent Smart Agriculture infrastructure.
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