Pub Date : 2024-11-13DOI: 10.1109/JSEN.2024.3467055
Qian Sun;Jialong Pang;Xiaoyi Wang;Zhiyao Zhao;Jing Li
Given the intrinsic low energy and high consumption characteristics of sensor nodes, it is imperative to explore strategies for achieving energy-efficient routing within wireless sensor networks (WSNs). A significant body of existing research on clustered routing algorithms for WSNs has concentrated on employing heuristic optimization algorithms to facilitate the selection of routing paths. However, once the number of sensor nodes or the deployment environment changes, the algorithm’s performance can fluctuate significantly, potentially requiring redesign and retuning. In this article, we propose the clustered routing algorithm based on forwarding mechanism optimization (CRFMO), which defines separate routing rules for intracluster and intercluster communication, providing suitable communication paths for nodes. The algorithm eschews the complex procedure of parameter tuning during the routing path selection process and contributes to expediting WSN deployment and balancing node load pressure, ultimately extending the network’s operational lifespan. Simulation outcomes reveal that, in comparison to LEACH-IACA and IMP-LEACH, the CRFMO algorithm markedly enhances energy distribution balance, equalizes the burden among nodes, sustains high network coverage over an extended period, which enhances the quality of network monitoring, and significantly extends the lifetime of the network.
{"title":"A Clustered Routing Algorithm Based on Forwarding Mechanism Optimization","authors":"Qian Sun;Jialong Pang;Xiaoyi Wang;Zhiyao Zhao;Jing Li","doi":"10.1109/JSEN.2024.3467055","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3467055","url":null,"abstract":"Given the intrinsic low energy and high consumption characteristics of sensor nodes, it is imperative to explore strategies for achieving energy-efficient routing within wireless sensor networks (WSNs). A significant body of existing research on clustered routing algorithms for WSNs has concentrated on employing heuristic optimization algorithms to facilitate the selection of routing paths. However, once the number of sensor nodes or the deployment environment changes, the algorithm’s performance can fluctuate significantly, potentially requiring redesign and retuning. In this article, we propose the clustered routing algorithm based on forwarding mechanism optimization (CRFMO), which defines separate routing rules for intracluster and intercluster communication, providing suitable communication paths for nodes. The algorithm eschews the complex procedure of parameter tuning during the routing path selection process and contributes to expediting WSN deployment and balancing node load pressure, ultimately extending the network’s operational lifespan. Simulation outcomes reveal that, in comparison to LEACH-IACA and IMP-LEACH, the CRFMO algorithm markedly enhances energy distribution balance, equalizes the burden among nodes, sustains high network coverage over an extended period, which enhances the quality of network monitoring, and significantly extends the lifetime of the network.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"38071-38081"},"PeriodicalIF":4.3,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-18DOI: 10.1109/JSEN.2024.3465606
Jun Chen;Zhixuan Su;Runze Lin;Kai Yang;Shuntao Hu;Shilong Liu;Yue Chen;Yihang Zhang;Chenyang Xue;Zhenyin Hai;Junyang Li
In the context of hyperthermal aerodynamics, where the heat transfer rate changes rapidly, there is an urgent need to obtain thermal data on the surface of structures. To address this, we propose a novel G-type coaxial dual-parametric sensor that utilizes the Seebeck thermoelectric effect to measure the temperature of high-temperature airflows and derive heat fluxes based on the 1-D semi-infinite body assumption method. In a laboratory environment, we performed static calibration of the sensor’s performance indices in the temperature range of $200~^{circ }$