{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T22:39:17Z","timestamp":1780094357723,"version":"3.54.0"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T00:00:00Z","timestamp":1731283200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T00:00:00Z","timestamp":1731283200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Vellore Institute of Technology, Vellore"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>Wireless Sensor Networks (WSN) are built with miniature sensor nodes (SN), which are deployed into the geographical location being sensed to monitor environmental conditions, which transfer the sensed physical information to the base station for further processing. The sensor nodes frequently experience node failure as a result of their hostile deployment and resource limitations. In WSN, node failure can cause a number of issues, namely Wireless Sensor Networks topology changes, broken communications links, disconnected portions of the network, and data transmission errors. An important concern of WSN is the detecting, diagnosing and recovering of sensor node failures. In the course of this effort, an effective strategy for sensor node failure detection algorithm using the Poisson Hidden Markov Model (PHMM) and the Fuzzy-based Chicken Swarm Optimization (F-CSO) is proposed for efficient detection of sensor node faults in the WSN. The proposed work offers optimal false alarm, false positive, energy consumption, detection accuracy, network lifetime, and least delay rates. Moreover, the F-CSO provides improved localization to locate the defective sensor nodes that are present in the WSN. The proposed work is implemented in the NS2 simulator with realistic simulation parameters, and the simulation results demonstrate that the proposed work is more effective in terms of 89.5% fault detection accuracy, 19.53% throughput, 8.43% energy consumption with minimum delay and less false positive rate when it is compared with other existing state-of-art systems.<\/jats:p>","DOI":"10.1038\/s41598-024-78646-2","type":"journal-article","created":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T08:11:15Z","timestamp":1731312675000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A fuzzy based chicken swarm optimization algorithm for efficient fault node detection in Wireless Sensor Networks"],"prefix":"10.1038","volume":"14","author":[{"given":"B","family":"Nagarajan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Santhosh Kumar","family":"SVN","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M","family":"Selvi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"K","family":"Thangaramya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,11,11]]},"reference":[{"key":"78646_CR1","doi-asserted-by":"crossref","unstructured":"Zhu, W. T., Zhou, J. & Bao, F. Detecting node replication attacks in wireless sensor networks: a survey. J. Netw. Comput. Appl. 35 (3), 1022\u20131034 (2012).","DOI":"10.1016\/j.jnca.2012.01.002"},{"issue":"2","key":"78646_CR2","first-page":"562","volume":"2","author":"J Cho","year":"2010","unstructured":"Cho, J., Swami, A. & Chen, I. A survey on trust management for mobile ad hoc networks. IEEE Commun. Surv. Tutorials. 2 (2), 562\u2013583 (2010).","journal-title":"IEEE Commun. Surv. Tutorials"},{"issue":"2","key":"78646_CR3","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/s10922-007-9062-0","volume":"15","author":"L Paradis","year":"2007","unstructured":"Paradis, L. & Han, Q. A survey of fault management in wireless sensor networks. J. Netw. Syst. Manage. 15 (2), 171\u2013190 (2007).","journal-title":"J. Netw. Syst. Manage."},{"issue":"4","key":"78646_CR4","doi-asserted-by":"publisher","first-page":"2927","DOI":"10.1007\/s11277-018-5981-1","volume":"103","author":"H Mosavvar","year":"2018","unstructured":"Mosavvar, H. & Ghaffari, A. Detecting faulty nodes in wireless sensor networks using harmony search algorithm. Wirel. Pers. Commun. 103 (4), 2927\u20132945. https:\/\/doi.org\/10.1007\/s11277-018-5981-1 (2018).","journal-title":"Wirel. Pers. Commun."},{"issue":"1","key":"78646_CR5","doi-asserted-by":"publisher","first-page":"629","DOI":"10.1007\/s11277-023-10627-6","volume":"132","author":"YM Raghavendra","year":"2023","unstructured":"Raghavendra, Y. M. & Mahadevaswamy, U. B. SBLDAR: a link score based delay aware routing for WSNS. Wireless Pers. Commun. 132 (1), 629\u2013650 (2023).","journal-title":"Wireless Pers. Commun."},{"key":"78646_CR6","doi-asserted-by":"crossref","unstructured":"Dinesh, K. & Santhosh Kumar, S. V. N. HBO-SROA: Honey Badger optimization based clustering with secured remora optimization based routing algorithm in wireless sensor networks. Peer-to-Peer Netw. Appl., 1\u201328. (2024).","DOI":"10.1007\/s12083-024-01708-9"},{"key":"78646_CR7","doi-asserted-by":"crossref","unstructured":"Raghavendra, Y. M. & Mahadevaswamy, U. B. Energy efficient routing in wireless sensor network based on mobile sink guided by stochastic hill climbing. Int. J. Electr. Comput. Eng. (IJECE). 10 (6), 5965\u20135973 (2020).","DOI":"10.11591\/ijece.v10i6.pp5965-5973"},{"issue":"10","key":"78646_CR8","doi-asserted-by":"publisher","first-page":"1487","DOI":"10.3390\/s16101487","volume":"16","author":"H Wang","year":"2016","unstructured":"Wang, H., Ding, X., Huang, C. & Wu, X. Adaptive connectivity restoration from node failure (s) in wireless sensor networks. Sensors. 16 (10), 1487 (2016).","journal-title":"Sensors"},{"issue":"9","key":"78646_CR9","doi-asserted-by":"publisher","first-page":"859","DOI":"10.17485\/ijst\/2015\/v8i9\/54915","volume":"8","author":"L Azari","year":"2015","unstructured":"Azari, L. & Ghaffari, A. Proposing a novel method based on network-coding for optimizing error recovery in wireless sensor networks. Indian J. Sci. Technol. 8 (9), 859\u2013867. https:\/\/doi.org\/10.17485\/ijst\/2015\/v8i9\/54915 (2015).","journal-title":"Indian J. Sci. Technol."},{"key":"78646_CR10","doi-asserted-by":"crossref","unstructured":"Swain, R. R., Khilar, P. M. & Bhoi, S. K. Heterogeneous fault diagnosis for wireless sensor networks, Ad Hoc Netw., vol. 69, pp. 15\u201337, Feb. (2018).","DOI":"10.1016\/j.adhoc.2017.10.012"},{"issue":"14","key":"78646_CR11","doi-asserted-by":"publisher","first-page":"1273","DOI":"10.1016\/S0140-3664(02)00030-0","volume":"25","author":"S Chessa","year":"2002","unstructured":"Chessa, S. & Santi, P. Crash faults identification in wireless sensor networks. Comput. Commun. 25 (14), 1273\u20131282 (2002).","journal-title":"Comput. Commun."},{"issue":"3","key":"78646_CR12","doi-asserted-by":"publisher","first-page":"1675","DOI":"10.1007\/s11277-023-10839-w","volume":"133","author":"YM Raghavendra","year":"2023","unstructured":"Raghavendra, Y. M., Mahadevaswamy, U. B., Asha, M. & Manjula, G. Energy Optimization in Spectrum sensing using Cognitive Radio Wireless Sensor Networks. Wireless Pers. Commun. 133 (3), 1675\u20131691 (2023).","journal-title":"Wireless Pers. Commun."},{"key":"78646_CR13","doi-asserted-by":"crossref","unstructured":"Swain, R. R., Khilar, P. M. & Dash, T. Multifault diagnosis in WSN using a hybrid metaheuristic trained neural network, Digit. Commun. Netw., vol. 6, no. 1, pp. 86\u2013100, Feb. (2020).","DOI":"10.1016\/j.dcan.2018.02.001"},{"issue":"3","key":"78646_CR14","doi-asserted-by":"publisher","first-page":"1374","DOI":"10.1111\/coin.12380","volume":"36","author":"S Mohapatra","year":"2020","unstructured":"Mohapatra, S. & Khilar, P. M. Fault diagnosis in wireless sensor network using negative selection algorithm and support vector machine. Comput. Intell. 36 (3), 1374\u20131393 (2020).","journal-title":"Comput. Intell."},{"issue":"4","key":"78646_CR15","doi-asserted-by":"publisher","first-page":"2000","DOI":"10.1109\/SURV.2013.030713.00062","volume":"15","author":"A Mahapatro","year":"2013","unstructured":"Mahapatro, A. & Khilar, P. M. Fault diagnosis in wireless sensor networks: a survey. IEEE Commun. Surv. Tutorials. 15 (4), 2000\u20132026 (2013).","journal-title":"IEEE Commun. Surv. Tutorials"},{"key":"78646_CR16","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1016\/j.comcom.2020.03.011","volume":"155","author":"E Moridi","year":"2020","unstructured":"Moridi, E., Haghparast, M., Hosseinzadeh, M. & Jassbi, S. J. Fault management frameworks in wireless sensor networks: a survey. Comput. Commun. 155, 205\u2013226 (2020).","journal-title":"Comput. Commun."},{"key":"78646_CR17","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1016\/j.jnca.2016.10.019","volume":"78","author":"T Muhammed","year":"2017","unstructured":"Muhammed, T. & Shaikh, R. A. An analysis of fault detection strategies in wireless sensor networks. J. Netw. Comput. Appl. 78, 267\u2013287 (2017).","journal-title":"J. Netw. Comput. Appl."},{"issue":"2","key":"78646_CR18","doi-asserted-by":"publisher","first-page":"837","DOI":"10.1007\/s11277-022-10158-6","volume":"129","author":"YM Raghavendra","year":"2023","unstructured":"Raghavendra, Y. M. & Mahadevaswamy, U. B. Hybrid rendezvous clustering model for efficient data collection in multi sink based wireless sensor networks. Wireless Pers. Commun. 129 (2), 837\u2013851 (2023).","journal-title":"Wireless Pers. Commun."},{"issue":"2","key":"78646_CR19","doi-asserted-by":"publisher","first-page":"1009","DOI":"10.1007\/s11277-021-08247-z","volume":"119","author":"YM Raghavendra","year":"2021","unstructured":"Raghavendra, Y. M. & Mahadevaswamy, U. B. Energy efficient intra cluster gateway optimal placement in wireless sensor network. Wireless Pers. Commun. 119 (2), 1009\u20131028 (2021).","journal-title":"Wireless Pers. Commun."},{"issue":"1","key":"78646_CR20","first-page":"1","volume":"1","author":"MS Rajan","year":"2021","unstructured":"Rajan, M. S. et al. Diagnosis of fault node in wireless sensor networks using adaptive neuro-fuzzy inference system. Appl. Nanosci. 1 (1), 1\u20139 (2021).","journal-title":"Appl. Nanosci."},{"issue":"1","key":"78646_CR21","doi-asserted-by":"publisher","first-page":"581","DOI":"10.1007\/s11277-019-06875-0","volume":"111","author":"M Masdari","year":"2020","unstructured":"Masdari, M. & \u00d6zdemir, S. Towards coverage-aware fuzzy logic-based faulty node detection in heterogeneous wireless sensor networks. Wireless Pers. Commun. 111 (1), 581\u2013610 (2020).","journal-title":"Wireless Pers. Commun."},{"key":"78646_CR22","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1016\/j.eswa.2015.09.040","volume":"45","author":"P Chanak","year":"2016","unstructured":"Chanak, P. & Banerjee, I. Fuzzy rule-based faulty node classification and management scheme for large scale wireless sensor networks. Expert Syst. Appl. 45, 307\u2013321 (2016).","journal-title":"Expert Syst. Appl."},{"key":"78646_CR23","doi-asserted-by":"crossref","unstructured":"Kaur, G. & Bhattacharya, M. Intelligent Fault diagnosis for AIT based Smart Farming Applications. IEEE Sens. J. (2023).","DOI":"10.1109\/JSEN.2023.3321417"},{"key":"78646_CR24","doi-asserted-by":"crossref","unstructured":"Moridi, E., Haghparast, M., Hosseinzadeh, M. & Jafarali Jassbi, S. Novel Fault Management Framework using Markov Chain in Wireless Sensor networks: FMMC. Wireless Pers. Commun. 114 (1), 583\u2013608 (2020).","DOI":"10.1007\/s11277-020-07383-2"},{"issue":"17","key":"78646_CR25","first-page":"1","volume":"8","author":"BS Kumar","year":"2021","unstructured":"Kumar, B. S. & Rao, P. T. An Optimal Emperor Penguin Optimization Based Enhanced Flower Pollination Algorithm in WSN for Fault Diagnosis and Prolong Network Lifespan. Wireless Pers. Commun. 8 (17), 1\u201318 (2021).","journal-title":"Wireless Pers. Commun."},{"key":"78646_CR26","doi-asserted-by":"crossref","unstructured":"Murthy, M. N. & Mahadevaswamy, U. B. R., Automatic fault identification in WSN-based smart grid environment. Int. J. Commun Syst, 35(18), e5340. (2022).","DOI":"10.1002\/dac.5340"},{"key":"78646_CR27","unstructured":"Thiyagarajan, R., Nagabhooshanam, N., Prasad, K. D. V. & Poojitha, P. A novel approach for missing data recovery and fault nodes detection in wireless sensor networks. Int. J. Commun Syst, e5924."},{"key":"78646_CR28","doi-asserted-by":"crossref","unstructured":"Swain, R. R., Khilar, P. M. & Dash, T. Multifault diagnosis in WSN using a hybrid metaheuristic trained neural network. Digit. Commun. Networks. 6 (1), 86\u2013100 (2020).","DOI":"10.1016\/j.dcan.2018.02.001"},{"issue":"5","key":"78646_CR29","doi-asserted-by":"publisher","first-page":"2901","DOI":"10.1007\/s11276-019-02005-7","volume":"25","author":"R Yarinezhad","year":"2019","unstructured":"Yarinezhad, R. & Hashemi, S. N. Distributed faulty node detection and recovery scheme for wireless sensor networks using cellular learning automata. Wireless Netw. 25 (5), 2901\u20132917 (2019).","journal-title":"Wireless Netw."},{"key":"78646_CR30","doi-asserted-by":"crossref","unstructured":"Palanikumar, R., Ramasamy, K. & Srinivasa Ragavan, P. Faulty node detection and recovery scheme for large-scale wireless sensor network using hosted cuckoo optimization algorithm. Int. J. Commun Syst, 35(9), e5143. (2022).","DOI":"10.1002\/dac.5143"},{"key":"78646_CR31","doi-asserted-by":"crossref","unstructured":"Gouda, B. S. et al. Distributed intermittent fault diagnosis in wireless sensor network using likelihood ratio test. IEEE Access. 11, 6958\u20136972 (2023).","DOI":"10.1109\/ACCESS.2023.3236880"},{"issue":"3","key":"78646_CR32","doi-asserted-by":"publisher","first-page":"592","DOI":"10.1080\/02664763.2021.1929089","volume":"50","author":"F Fan","year":"2023","unstructured":"Fan, F., Chu, S. C., Pan, J. S., Lin, C. & Zhao, H. An optimized machine learning technology scheme and its application in fault detection in wireless sensor networks. J. Appl. Stat. 50 (3), 592\u2013609 (2023).","journal-title":"J. Appl. Stat."},{"key":"78646_CR33","doi-asserted-by":"crossref","unstructured":"Kaur, G. & Bhattacharya, M. Green Fault tolerant AIoT-enabled Mobile Sink Data Collection Scheme in Sensor Networks. IEEE Trans. Veh. Technol. (2024).","DOI":"10.1109\/TVT.2024.3400880"},{"key":"78646_CR34","doi-asserted-by":"crossref","unstructured":"Prasanth, A. Certain investigations on energy-efficient fault detection and recovery management in underwater wireless sensor networks. J. Circuits Syst. Computers. 30 (08), 2150137 (2021).","DOI":"10.1142\/S0218126621501371"},{"key":"78646_CR35","doi-asserted-by":"publisher","first-page":"109771","DOI":"10.1016\/j.measurement.2021.109771","volume":"183","author":"S Lavanya","year":"2021","unstructured":"Lavanya, S., Prasanth, A., Jayachitra, S. & Shenbagarajan, A. A tuned classification approach for efficient heterogeneous fault diagnosis in IoT-enabled WSN applications. Measurement. 183, 109771 (2021).","journal-title":"Measurement"},{"issue":"2","key":"78646_CR36","doi-asserted-by":"publisher","first-page":"763","DOI":"10.1007\/s11277-019-06884-z","volume":"111","author":"RR Swain","year":"2020","unstructured":"Swain, R. R., Khilar, P. M. & Bhoi, S. K. Underlying and persistence fault diagnosis in wireless sensor networks using majority neighbors co-ordination approach. Wireless Pers. Commun. 111 (2), 763\u2013798 (2020).","journal-title":"Wireless Pers. Commun."},{"key":"78646_CR37","doi-asserted-by":"crossref","unstructured":"Jia, S., Ma, L. & Qin, D. Fault detection modelling and analysis in a wireless sensor network. Journal of Sensors, 2018. (2018).","DOI":"10.1155\/2018\/7935802"},{"issue":"2","key":"78646_CR38","doi-asserted-by":"publisher","first-page":"616","DOI":"10.1016\/j.gene.2013.06.052","volume":"527","author":"J Lu","year":"2013","unstructured":"Lu, J. & Bushel, P. R. Dynamic expression of 3\u2032 UTRs revealed by Poisson hidden Markov modeling of RNA-Seq: implications in gene expression profiling. Gene. 527 (2), 616\u2013623 (2013).","journal-title":"Gene"},{"issue":"10","key":"78646_CR39","doi-asserted-by":"publisher","first-page":"2529","DOI":"10.1016\/j.comnet.2006.11.018","volume":"51","author":"G Mao","year":"2007","unstructured":"Mao, G., Fidan, B. & Anderson, B. D. Wireless sensor network localization techniques. Comput. Netw. 51 (10), 2529\u20132553 (2007).","journal-title":"Comput. Netw."},{"issue":"4","key":"78646_CR40","doi-asserted-by":"publisher","first-page":"5691","DOI":"10.1007\/s11277-017-4803-1","volume":"97","author":"M Al Shayokh","year":"2017","unstructured":"Al Shayokh, M. & Shin, S. Y. Bio inspired distributed WSN localization based on chicken swarm optimization. Wireless Pers. Commun. 97 (4), 5691\u20135706 (2017).","journal-title":"Wireless Pers. Commun."},{"key":"78646_CR41","doi-asserted-by":"crossref","unstructured":"Meng, X., Liu, Y., Gao, X. & Zhang, H. A new bio-inspired algorithm: chicken swarm optimization. In International conference in swarm intelligence (pp. 86\u201394). Springer, Cham. (2014), October.","DOI":"10.1007\/978-3-319-11857-4_10"},{"key":"78646_CR42","doi-asserted-by":"crossref","unstructured":"Wang, Z., Qin, C., Wan, B., Song, W. W. & Yang, G. An Adaptive Fuzzy Chicken Swarm Optimization Algorithm. Mathematical Problems in Engineering, 2021. (2021).","DOI":"10.1155\/2021\/8896794"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-024-78646-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-024-78646-2","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-024-78646-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,15]],"date-time":"2025-04-15T10:56:40Z","timestamp":1744714600000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-024-78646-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,11]]},"references-count":42,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["78646"],"URL":"https:\/\/doi.org\/10.1038\/s41598-024-78646-2","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,11]]},"assertion":[{"value":"12 August 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 November 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 November 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Research involving human participants and\/or animals"}}],"article-number":"27532"}}