Optimizing energy efficiency in WSNs through dynamic sensor deployment and advanced clustering

Abstract

Wireless sensor networks (WSNs) have revolutionized data capture and utilization in agricultural fields. With the potential to incorporate thousands of nodes, WSNs enable agile sensing and communication. However, the limited life cycle of the sensor nodes and their energy sources pose a significant challenge. Maximizing their utilization and efficiency becomes paramount. This paper presents an advanced deterministic energy-efficient clustering protocol that selects cluster heads to extend the lifespan of sensor nodes. Our algorithm intelligently selects the cluster heads, improving the overall lifespan of the network considering the position, distance, and residual energy of the nodes. This approach addresses the primary concern of efficient energy use in WSNs. To assess the efficiency of our proposed protocol, we conducted fifty simulations using the NS3 simulator, employing the advanced deterministic energy-efficient clustering algorithm. We analyze the simulation results to show the effectiveness and efficiency of our approach. Unlike many existing probabilistic routing protocols that rely solely on residual energy, our architecture incorporates a dynamic approach to calculate the number of sensors required for complete field coverage. In addition, we devised a routing protocol that intelligently selects cluster heads, optimizing communication within the network. The ADEC protocol optimizes the utilization of the sensor nodes by calculating the number of sensors required based on the area and the range of detection. For example, in a 100x100-meter area, our algorithm determines that only 74 sensors are required, compared to the previous requirement of 100 sensors. This method allows users to input an initial field area (e.g. 100x100 meters) and subsequently provide new values for multiple simulations (e.g., 120x120 meters), ensuring that all simulations follow the specified sequence. The algorithm dynamically adjusts the sensor count for each area, extending the WSN’s lifespan by significantly delaying the last node’s failure.