A Load-Balancing and Energy-Efficient Routing Protocol Based on Multi-Factor Ant Colony Optimization for WSNs

Abstract

: The Wireless Sensor Networks (WSNs), serving as the perception layer of the Internet of Things (IoT), play a vital role in various fields such as environmental monitoring, smart homes, and industrial automation. However, the limited battery capacity of sensor nodes and the uneven traffic burden caused by multi-hop transmission often lead to premature node death, energy holes, and network partitioning. To address these problems, this paper proposes an Energy-efficient and Load-balanced Routing protocol based on Ant Colony optimization (ELRAC). First, a hierarchical regional network model and an angle-based neighbor pre-screening mechanism are designed to reduce ineffective node interactions and avoid backward or detoured forwarding. Second, a composite heuristic function integrating distance, directional angle, and residual energy is constructed to guide ants toward energy-efficient and load-balanced next-hop selection. Third, a dynamic pheromone replenishment mechanism is introduced to maintain route diversity and alleviate premature convergence. Simulation experiments are conducted under different network settings and compared with representative routing protocols, including LEACH, R-LEACH, GWOA-CH, and AEGWO-CH. The results show that ELRAC improves packet delivery, energy utilization, and overall routing stability while maintaining a balanced network lifetime. These results demonstrate that the proposed protocol can effectively enhance load balancing and energy-efficient routing performance in WSNs.