{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T11:21:17Z","timestamp":1780053677976,"version":"3.54.0"},"reference-count":33,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T00:00:00Z","timestamp":1751500800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Commun. Netw."],"abstract":"<jats:p>Wireless sensor networks (WSNs) are extensively employed in various applications like environmental monitoring, healthcare, and industrial automation. However, their performance is severely affected by energy limitations and unreliable data communication because of low battery capacity and dynamic network scenarios. Optimal cluster head (CH) selection is one of the major challenges in WSNs, and it is a critical factor in network lifetime and energy efficiency. The proposed work introduces a clustering mechanism and self-healing and energy-efficient cluster-based routing (SHEER) for CH selection by considering various parameters like energy remaining, distance to the sink, and the trust metric. In contrast to traditional approaches, the proposed method not only maximizes CH selection but also enhances cluster member (CM) distribution for balanced energy consumption. Moreover, a self-healing mechanism is integrated to preserve network stability by dynamically redistributing CHs and CMs in the event of node failure. This increases network flexibility, minimizes energy loss, and extends network lifetime. To confirm the proposed strategy, a large-scale simulation is performed in Cooja software using 100 to 500 sensor nodes. The outcome showed that the proposed SHEER technique enhances WSN performance with a 98% packet delivery ratio (PDR), a 2% packet loss ratio (PLR), and less energy consumption while maintaining stable clusters. These results show that the clustering optimization technique significantly improves the energy efficiency, network lifetime, and data transmission reliability, ensuring a high packet delivery ratio.<\/jats:p>","DOI":"10.3389\/frcmn.2025.1602928","type":"journal-article","created":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T10:59:08Z","timestamp":1751540348000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Self-healing and energy-efficient cluster-based routing for sustainable wireless sensor networks"],"prefix":"10.3389","volume":"6","author":[{"family":"Gayathri M","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vanapalli","family":"Veera Snigdha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,7,3]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"70849","DOI":"10.1109\/ACCESS.2025.3562368","article-title":"EEMLCR: energy-efficient machine learning-based clustering and routing for wireless sensor networks","volume":"13","author":"Akram","year":"2025","journal-title":"IEEE Access"},{"key":"B2","doi-asserted-by":"publisher","first-page":"77","DOI":"10.3390\/fi9040077","article-title":"A comprehensive survey on real-time applications of WSN","volume":"9","author":"Ali","year":"2017","journal-title":"Future Internet"},{"key":"B3","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1109\/mwc.2004.1368893","article-title":"Routing techniques in wireless sensor networks: a survey","volume":"11","author":"Al-Karaki","year":"2004","journal-title":"IEEE Wirel. 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