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本文引用的文献

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Node Role Selection and Rotation Scheme for Energy Efficiency in Multi-Level IoT-Based Heterogeneous Wireless Sensor Networks (HWSNs).基于多级物联网的异构无线传感器网络(HWSN)中用于能源效率的节点角色选择与轮换方案
Sensors (Basel). 2024 Aug 30;24(17):5642. doi: 10.3390/s24175642.
2
An Event-Aware Cluster-Head Rotation Algorithm for Extending Lifetime of Wireless Sensor Network with Smart Nodes.具有智能节点的延长无线传感器网络生命周期的事件感知簇头轮换算法。
Sensors (Basel). 2019 Sep 20;19(19):4060. doi: 10.3390/s19194060.
3
Energy Consumption Model for Sensor Nodes Based on LoRa and LoRaWAN.基于 LoRa 和 LoRaWAN 的传感器节点能耗模型。
Sensors (Basel). 2018 Jun 30;18(7):2104. doi: 10.3390/s18072104.
4
Modeling the Energy Performance of LoRaWAN.对LoRaWAN的能源性能进行建模。
Sensors (Basel). 2017 Oct 16;17(10):2364. doi: 10.3390/s17102364.

一种用于延长无线传感器网络中最后节点寿命的簇头选择算法。

A Cluster Head Selection Algorithm for Extending Last Node Lifetime in Wireless Sensor Networks.

作者信息

Lewandowski Marcin, Płaczek Bartłomiej

机构信息

Institute of Computer Science, University of Silesia, Będzińska 39, 41-200 Sosnowiec, Poland.

出版信息

Sensors (Basel). 2025 May 30;25(11):3466. doi: 10.3390/s25113466.

DOI:10.3390/s25113466
PMID:40969043
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12158193/
Abstract

This paper introduces a new cluster head selection algorithm for wireless sensor networks (WSNs) to maximize the time until the last sensor node depletes its energy. The algorithm is based on a formal analysis in which network lifetime is modeled as a function of node energy consumption. In contrast to existing energy-balancing strategies, this analytical foundation leads to a distinctive selection rule that prioritizes the node with the highest transmission probability and the lowest initial energy as the initial cluster head. The algorithm employs distributed per-cluster computation, enabling scalability without increasing complexity relative to network size. Unlike traditional approaches that rotate cluster heads based on time or equal energy use, our method adapts to heterogeneous energy consumption patterns and enforces a cluster head rotation order that maximizes the lifetime of the final active node. To validate the effectiveness of the proposed approach, we implement it on a real-world LoRaWAN-based sensor network prototype. Experimental results demonstrate that our method significantly extends the lifetime of the last active node compared to representative state-of-the-art algorithms. This research provides a practical and robust solution for energy-efficient WSN operation in real deployment scenarios by considering realistic and application-driven communication behavior along with hardware-level energy consumption.

摘要

本文介绍了一种用于无线传感器网络(WSN)的新簇头选择算法,以最大化直到最后一个传感器节点耗尽能量的时间。该算法基于形式分析,其中将网络寿命建模为节点能量消耗的函数。与现有的能量平衡策略不同,这种分析基础导致了一种独特的选择规则,该规则将具有最高传输概率和最低初始能量的节点优先作为初始簇头。该算法采用分布式的每簇计算,相对于网络规模,在不增加复杂度的情况下实现了可扩展性。与基于时间或等能量使用来轮换簇头的传统方法不同,我们的方法适应异构能量消耗模式,并强制执行一种簇头轮换顺序,以使最终活跃节点的寿命最大化。为了验证所提方法的有效性,我们在基于LoRaWAN的真实世界传感器网络原型上实现了该算法。实验结果表明,与具有代表性的最先进算法相比,我们的方法显著延长了最后活跃节点的寿命。本研究通过考虑实际且应用驱动的通信行为以及硬件级能量消耗,为实际部署场景中高效节能的WSN运行提供了一种实用且稳健的解决方案。