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Article

A Dynamic Clustering Routing Protocol for Multi-Source Forest Sensor Networks

1
Energy Management Section, Logistics Management Department, Nanjing Forestry University, Nanjing 210037, China
2
College of Information Science and Technology & Artificial Intelligence, Nanjing Forestry University, Nanjing 210037, China
*
Author to whom correspondence should be addressed.
Forests 2026, 17(1), 62; https://doi.org/10.3390/f17010062
Submission received: 27 November 2025 / Revised: 28 December 2025 / Accepted: 29 December 2025 / Published: 31 December 2025
(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)

Abstract

The use of wireless sensor networks (WSNs) enables multidimensional and high-precision forest environment monitoring around the clock. However, the limited energy supply of sensor nodes using solely batteries is insufficient to support long-term data collection. Furthermore, since the complex terrain, dense vegetation, and variable weather in forests present unique challenges, relying on a single energy source is insufficient to ensure a stable energy supply for sensor nodes. Combining multiple energy sources is a promising way which has not been well studied. In this paper, to effectively utilize multiple energy sources, we propose a novel dynamic clustering routing protocol which considers the inherent diversity and intermittency of energy sources of the WSN in the forest. First, to address the inconsistency in residual energy caused by uneven energy harvesting among sensor nodes, a cluster head selection weight function is developed, and a dynamic weight-based cluster head election algorithm is proposed. This mechanism effectively prevents low-energy nodes from being selected as cluster heads, thereby maximizing the utilization of harvested energy. Second, a Q-learning-based adaptive hybrid transmission scheme is introduced, integrating both single-hop and multi-hop communication. The scheme dynamically optimizes intra-cluster transmission paths based on the current network state, reducing energy consumption during data transmission. The simulation results show that the proposed routing algorithm significantly outperforms existing methods in total network energy consumption, network lifetime, and energy balance. These advantages make it particularly suitable for forest environments characterized by strong fluctuations in harvested energy. In summary, this work provides an energy-efficient and adaptive routing solution suitable for forest environments with fluctuating energy availability.
Keywords: wireless sensor network; energy harvesting; energy prediction algorithm; cluster routing wireless sensor network; energy harvesting; energy prediction algorithm; cluster routing

Share and Cite

MDPI and ACS Style

Yu, W.; Wang, Z.; Jiao, W. A Dynamic Clustering Routing Protocol for Multi-Source Forest Sensor Networks. Forests 2026, 17, 62. https://doi.org/10.3390/f17010062

AMA Style

Yu W, Wang Z, Jiao W. A Dynamic Clustering Routing Protocol for Multi-Source Forest Sensor Networks. Forests. 2026; 17(1):62. https://doi.org/10.3390/f17010062

Chicago/Turabian Style

Yu, Wenrui, Zehui Wang, and Wanguo Jiao. 2026. "A Dynamic Clustering Routing Protocol for Multi-Source Forest Sensor Networks" Forests 17, no. 1: 62. https://doi.org/10.3390/f17010062

APA Style

Yu, W., Wang, Z., & Jiao, W. (2026). A Dynamic Clustering Routing Protocol for Multi-Source Forest Sensor Networks. Forests, 17(1), 62. https://doi.org/10.3390/f17010062

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