{"title":"增强无线传感器网络性能:一种新的自适应网格聚类层次协议","authors":"Mohammad Ridwan , Teguh Wahyono , Irwan Sembiring , Rini Darmastuti","doi":"10.1016/j.array.2025.100440","DOIUrl":null,"url":null,"abstract":"<div><div>Wireless Sensor Networks (WSNs) are essential for data collection in remote and energy-constrained environments such as forests and deserts. However, traditional clustering protocols like LEACH often face limitations including uneven energy consumption, inefficient Cluster Head (CH) selection, and high communication overhead, which collectively degrade network performance. This paper introduces AG-LEACH (Adaptive Grid-Based LEACH), a novel clustering protocol that incorporates dynamic grid partitioning to optimize cluster formation, CH selection, and data transmission. AG-LEACH employs adaptive grid sizing, adaptive grid merging, and adaptive cluster head selection, enabling dynamic responses to variations in node energy and network topology changes. Simulation results demonstrate that AG-LEACH outperforms conventional protocols by maintaining higher energy efficiency, prolonging network lifetime, and improving data throughput while minimizing packet loss. The protocol also reduces communication distance by intelligently routing data, leading to lower transmission energy and latency. These findings indicate that AG-LEACH is a scalable and adaptive solution for energy-efficient WSN deployments, with strong potential for real-world applications in large-scale and dynamic sensing environments.</div></div>","PeriodicalId":8417,"journal":{"name":"Array","volume":"27 ","pages":"Article 100440"},"PeriodicalIF":4.5000,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhancing Wireless Sensor Network performance: A Novel Adaptive Grid-Based Clustering Hierarchy protocol\",\"authors\":\"Mohammad Ridwan , Teguh Wahyono , Irwan Sembiring , Rini Darmastuti\",\"doi\":\"10.1016/j.array.2025.100440\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Wireless Sensor Networks (WSNs) are essential for data collection in remote and energy-constrained environments such as forests and deserts. However, traditional clustering protocols like LEACH often face limitations including uneven energy consumption, inefficient Cluster Head (CH) selection, and high communication overhead, which collectively degrade network performance. This paper introduces AG-LEACH (Adaptive Grid-Based LEACH), a novel clustering protocol that incorporates dynamic grid partitioning to optimize cluster formation, CH selection, and data transmission. AG-LEACH employs adaptive grid sizing, adaptive grid merging, and adaptive cluster head selection, enabling dynamic responses to variations in node energy and network topology changes. Simulation results demonstrate that AG-LEACH outperforms conventional protocols by maintaining higher energy efficiency, prolonging network lifetime, and improving data throughput while minimizing packet loss. The protocol also reduces communication distance by intelligently routing data, leading to lower transmission energy and latency. These findings indicate that AG-LEACH is a scalable and adaptive solution for energy-efficient WSN deployments, with strong potential for real-world applications in large-scale and dynamic sensing environments.</div></div>\",\"PeriodicalId\":8417,\"journal\":{\"name\":\"Array\",\"volume\":\"27 \",\"pages\":\"Article 100440\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2025-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Array\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2590005625000670\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Array","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590005625000670","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
摘要
无线传感器网络(wsn)对于在森林和沙漠等偏远和能源受限的环境中收集数据至关重要。然而,像LEACH这样的传统聚类协议经常面临一些限制,包括不均匀的能耗、低效的簇头(CH)选择和高通信开销,这些都会降低网络性能。本文介绍了一种新的聚类协议AG-LEACH (Adaptive grid - based LEACH),该协议采用动态网格划分来优化聚类形成、CH选择和数据传输。AG-LEACH采用自适应网格大小、自适应网格合并和自适应簇头选择,能够对节点能量和网络拓扑变化的变化做出动态响应。仿真结果表明,AG-LEACH在保持更高的能量效率、延长网络生命周期、提高数据吞吐量和最小化丢包方面优于传统协议。该协议还通过智能路由数据来缩短通信距离,从而降低传输能量和延迟。这些发现表明AG-LEACH是一种可扩展和自适应的节能WSN部署解决方案,在大规模和动态传感环境中具有强大的实际应用潜力。
Wireless Sensor Networks (WSNs) are essential for data collection in remote and energy-constrained environments such as forests and deserts. However, traditional clustering protocols like LEACH often face limitations including uneven energy consumption, inefficient Cluster Head (CH) selection, and high communication overhead, which collectively degrade network performance. This paper introduces AG-LEACH (Adaptive Grid-Based LEACH), a novel clustering protocol that incorporates dynamic grid partitioning to optimize cluster formation, CH selection, and data transmission. AG-LEACH employs adaptive grid sizing, adaptive grid merging, and adaptive cluster head selection, enabling dynamic responses to variations in node energy and network topology changes. Simulation results demonstrate that AG-LEACH outperforms conventional protocols by maintaining higher energy efficiency, prolonging network lifetime, and improving data throughput while minimizing packet loss. The protocol also reduces communication distance by intelligently routing data, leading to lower transmission energy and latency. These findings indicate that AG-LEACH is a scalable and adaptive solution for energy-efficient WSN deployments, with strong potential for real-world applications in large-scale and dynamic sensing environments.