{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T08:55:50Z","timestamp":1767084950043,"version":"build-2065373602"},"reference-count":19,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2015,12,22]],"date-time":"2015-12-22T00:00:00Z","timestamp":1450742400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>As wireless sensor network (WSN) is often deployed in a hostile environment, nodes in the networks are prone to large-scale failures, resulting in the network not working normally. In this case, an effective restoration scheme is needed to restore the faulty network timely. Most of existing restoration schemes consider more about the number of deployed nodes or fault tolerance alone, but fail to take into account the fact that network coverage and topology quality are also important to a network. To address this issue, we present two algorithms named Full 2-Connectivity Restoration Algorithm (F2CRA) and Partial 3-Connectivity Restoration Algorithm (P3CRA), which restore a faulty WSN in different aspects. F2CRA constructs the fan-shaped topology structure to reduce the number of deployed nodes, while P3CRA constructs the dual-ring topology structure to improve the fault tolerance of the network. F2CRA is suitable when the restoration cost is given the priority, and P3CRA is suitable when the network quality is considered first. Compared with other algorithms, these two algorithms ensure that the network has stronger fault-tolerant function, larger coverage area and better balanced load after the restoration.<\/jats:p>","DOI":"10.3390\/s16010003","type":"journal-article","created":{"date-parts":[[2015,12,23]],"date-time":"2015-12-23T06:52:19Z","timestamp":1450853539000},"page":"3","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Fault-Tolerant Algorithms for Connectivity Restoration in Wireless Sensor Networks"],"prefix":"10.3390","volume":"16","author":[{"given":"Yali","family":"Zeng","sequence":"first","affiliation":[{"name":"Fujian Provincial Key Laboratory of Network Security and Cryptology, School of Mathematics and Computer Science, Fujian Normal University, Fuzhou 350007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Xu","sequence":"additional","affiliation":[{"name":"Fujian Provincial Key Laboratory of Network Security and Cryptology, School of Mathematics and Computer Science, Fujian Normal University, Fuzhou 350007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhide","family":"Chen","sequence":"additional","affiliation":[{"name":"Fujian Provincial Key Laboratory of Network Security and Cryptology, School of Mathematics and Computer Science, Fujian Normal University, Fuzhou 350007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2015,12,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4072","DOI":"10.3390\/s150204072","article-title":"Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases","volume":"15","author":"Malaver","year":"2015","journal-title":"Sensors"},{"key":"ref_2","unstructured":"Hao, B., Tang, J., and Xue, G. 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