Wang Rui, Guo Xiaoling, Sun Xinghua, Yang Jie
School of Information Science and Engineering, Hebei North University, Zhangjiakou, 075000, China.
Faculty of Science, Hebei North University, Zhangjiakou, 075000, China.
Sci Rep. 2025 Apr 11;15(1):12517. doi: 10.1038/s41598-025-96613-3.
In the large scale monitoring application of the IoT, the power carried by a single sensor node is limited, and it may not be replenished in the later stage. Therefore, it is required that the sensor nodes should save power when working, and the power consumption among the sensor nodes should be balanced to avoid the early death of some nodes and the occurrence of monitoring blind spots in the monitor area. Communication is the main part of power loss for sensor nodes. For this reason, this paper introduces a new low power energy balanced clustering routing scheme. Firstly, the sparrow search algorithm is improved by adding adaptive sine function and Cauchy random number to raise the search capability of the discoverer; The standard normal distribution random number is used to enhance the vigilant escape from the limit of local optimal value. Then the enhanced SSA algorithm can be used for cluster head selection. A fitness function with five key parameters is constructed by using the residual energy, the member number within a cluster, the intra-cluster distance in a cluster, the distance among clusters, and the distance from cluster head to base station, which effectively realizes the energy consumption balance among sensors in each round. At the same time, in the data forwarding stage, the multi-hop forwarding rules are designed to further reduce energy loss, greatly delay the arrival of the first dead node, and keep the sensor node working in the low power mode for a long time. Experimental results show that this scheme not only significantly prolongs the sensor lifetime, but also balances the power consumption among sensor nodes. This scheme provides a new idea for IoT sensor nodes to work in low power and ultra long standby mode, especially suitable for large scale and long term deployment scenarios such as ecological monitoring and industrial equipment state perception.
在物联网的大规模监测应用中，单个传感器节点所携带的能量有限，且后期可能无法补充。因此，要求传感器节点在工作时应节约能量，并且传感器节点之间的能量消耗要平衡，以避免部分节点过早死亡以及监测区域出现监测盲点。通信是传感器节点能量损耗的主要部分。为此，本文提出一种新的低功耗能量均衡聚类路由方案。首先，通过添加自适应正弦函数和柯西随机数对麻雀搜索算法进行改进，以提高发现者的搜索能力；利用标准正态分布随机数增强警惕性，使其逃离局部最优值的限制。然后，将改进后的麻雀搜索算法用于簇头选择。通过剩余能量、簇内成员数量、簇内簇内距离、簇间距离以及簇头到基站的距离这五个关键参数构建适应度函数，有效实现了每一轮中传感器之间的能量消耗平衡。同时，在数据转发阶段，设计多跳转发规则以进一步降低能量损耗，大大延迟首个死亡节点的出现，并使传感器节点长时间处于低功耗模式工作。实验结果表明，该方案不仅显著延长了传感器寿命，还平衡了传感器节点之间的能量消耗。该方案为物联网传感器节点以低功耗和超长待机模式工作提供了新思路，尤其适用于生态监测和工业设备状态感知等大规模、长期部署场景。
