An Artificial Intelligence-Based Energy-Efficient Approach for Wireless Sensor Networks Enabled IoT

Wireless sensor networks (WSNs) and Internet of Things (IoT) involve numerous small sensor nodes (SNs) running on batteries, expending energy in data routing towards the sink. An efficient routing scheme is crucial for WSN longevity. In WSN routing, minimizing routing hops conflicts with inter-hop routing distance—fewer hops may increase distance and vice versa. To address this, we introduce a new multi-objective biogeography-based optimization algorithm (MOBBO-R) aiming to optimize both routing objectives and reduce energy consumption in WSNs. MOBBO-R seeks a Pareto optimal solution, prolonging WSN lifetime by enhancing routing efficiency. Validated through MATLAB, MOBBO-R outperforms past routing algorithms like PSO routing and neighbourhood routing by approximately 7% and 22%, respectively. This algorithm holds promise for various IoT and IoE-based applications globally.