Energy efficient multi hop clustering using Artificial Bee Colony metaheuristic in WSN
Shiwei Zhang, Xinghan Liu, Mohammad Trik
Abstract
Wireless sensor networks (WSNs) have garnered considerable interest for their ability to gather and transmit data in applications including environmental monitoring, industrial automation, and military surveillance. The constrained energy supply of sensors, frequently dependent on non-rechargeable batteries, presents a significant issue in the design and efficacy of these networks. This paper introduces EEM-LEACH-ABC, a novel energy-efficient clustering and routing protocol for WSNs using the Artificial Bee Colony (ABC) algorithm. The protocol integrates three main mechanisms of region-based energy-aware clustering using network partitioning, optimized multi-hop communication paths, and a hierarchical tree structure for efficient data aggregation. ABC dynamically selects Cluster Heads (CHs) and routing paths based on key parameters including residual energy, transmission distance, Cluster Head Ratio (CR), and multi-objective weighting coefficients. Simulation results under different scenarios - including centralized, edge, and corner base station placements - show that EEM-LEACH-ABC outperforms existing protocols such as MHCRP, SBOA, and HChOA in terms of First Node Death (FND), Half Node Death (HND), Packet Delivery Ratio (PDR), and energy consumption. Specifically, the protocol achieves up to 216% improvement in FND and 29% increase in packet delivery at the base station. Furthermore, the protocol adapts to interference, node failures, and mobile sensor nodes, thereby ensuring robustness and scalability in real-world deployments. Parameters are automatically optimized using ABC to minimize energy imbalance and increase network lifetime.