{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T15:49:22Z","timestamp":1772725762213,"version":"3.50.1"},"reference-count":15,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Wireless Pers Commun"],"published-print":{"date-parts":[[2024,11]]},"DOI":"10.1007\/s11277-024-11680-5","type":"journal-article","created":{"date-parts":[[2024,12,10]],"date-time":"2024-12-10T07:00:01Z","timestamp":1733814001000},"page":"1285-1301","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Clustering-Cum-Classification Based Machine Learning Medium Access Control Protocol for Three Tier Heterogeneous Wireless Sensor Network"],"prefix":"10.1007","volume":"139","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4803-0968","authenticated-orcid":false,"given":"Yogesh","family":"Patidar","sequence":"first","affiliation":[]},{"given":"Manish","family":"Jain","sequence":"additional","affiliation":[]},{"given":"Ajay Kumar","family":"Vyas","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,12,10]]},"reference":[{"key":"11680_CR1","doi-asserted-by":"publisher","first-page":"110762","DOI":"10.1109\/ACCESS.2021.3102859","volume":"9","author":"MM Rooney","year":"2021","unstructured":"Rooney, M. M., & Hinders, M. K. (2021). Machine learning for medium access control protocol recognition in communications networks. IEEE Access, 9, 110762\u2013110771. https:\/\/doi.org\/10.1109\/ACCESS.2021.3102859","journal-title":"IEEE Access"},{"key":"11680_CR2","doi-asserted-by":"publisher","unstructured":"Singh Nayak, N. K., & Bhattacharyya, B. (2021) \"Machine learning-based medium access control protocol for heterogeneous wireless networks: A review,\" 2021 Innovations in Power and Advanced Computing Technologies (i-PACT), Kuala Lumpur, Malaysia, pp. 1-6, https:\/\/doi.org\/10.1109\/i-PACT52855.2021.9696964.","DOI":"10.1109\/i-PACT52855.2021.9696964"},{"key":"11680_CR3","doi-asserted-by":"publisher","unstructured":"PK, M. K., Hossain, A. A., Al Majmaie, S., & Amsaad, F., (2024) \"Routing protocol attack detection using machine learning through parallel computing in wireless sensor network,\" In 2024 IEEE 3rd International Conference on Computing and Machine Intelligence (ICMI), Mt Pleasant, MI, USA, pp. 1\u20135, https:\/\/doi.org\/10.1109\/ICMI60790.2024.10586175.","DOI":"10.1109\/ICMI60790.2024.10586175"},{"key":"11680_CR4","doi-asserted-by":"publisher","unstructured":"Nawkhare, R., & Singh, D. (2022) \"Machine learning approach on efficient routing efficient techniques in wireless sensor network,\" In 2022 IEEE International Conference on Current Development in Engineering and Technology (CCET), Bhopal, India, pp. 1\u20136, https:\/\/doi.org\/10.1109\/CCET56606.2022.10080050.","DOI":"10.1109\/CCET56606.2022.10080050"},{"key":"11680_CR5","doi-asserted-by":"crossref","unstructured":"Shafiullah, G. M., Thompson, A., Wolfs, P. J., & Ali, S. (2008) \u201cEnergy-efficient TDMA MAC protocol for wireless sensor networks applications,\u201d in Proc. 5th ICECE, Dhaka, Bangladesh, Dec. 24\u201327, pp. 85\u201390.","DOI":"10.1109\/ICCITECHN.2008.4803131"},{"issue":"2","key":"11680_CR6","doi-asserted-by":"publisher","first-page":"649","DOI":"10.1109\/TITS.2012.2227315","volume":"14","author":"G Shafiullah","year":"2013","unstructured":"Shafiullah, G., Azad, S. A., & Ali, A. B. M. S. (2013). Energy-efficient wireless MAC protocols for railway monitoring applications. IEEE Transactions on Intelligent Transportation Systems, 14(2), 649\u2013659.","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"11680_CR7","doi-asserted-by":"crossref","unstructured":"Li, J., & Lazarou, G. Y. (2004) \"A bit-map-assisted energy-efficient MAC scheme for wireless sensor networks,\" Third International Symposium on Information Processing in Sensor Networks, IPSN 2004, pp. 55\u201360.","DOI":"10.1145\/984622.984631"},{"key":"11680_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/s42979-020-00162-7","author":"M Tolani","year":"2020","unstructured":"Tolani, M., Sunny, R. K., & Singh. (2020). Adaptive duty-cycle-enabled energy-efficient bit-map-assisted MAC protocol. SN Computer Science. https:\/\/doi.org\/10.1007\/s42979-020-00162-7","journal-title":"SN Computer Science"},{"key":"11680_CR9","doi-asserted-by":"publisher","unstructured":"Gantassi, R., Masood, Z., Lim, S., Sias, Q. A., & Choi, Y., (2023) \"Performance analysis of machine learning algorithms with clustering protocol in wireless sensor networks,\" In 2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), Bali, Indonesia, pp. 543\u2013546, https:\/\/doi.org\/10.1109\/ICAIIC57133.2023.10067019.","DOI":"10.1109\/ICAIIC57133.2023.10067019"},{"issue":"2","key":"11680_CR10","doi-asserted-by":"publisher","first-page":"1251","DOI":"10.1109\/COMST.2020.2964534","volume":"22","author":"F Hussain","year":"2020","unstructured":"Hussain, F., Hassan, S. A., Hussain, R., & Hossain, E. (2020). Machine learning for resource management in cellular and IoT networks: potentials current solutions and open challenges. IEEE Communications Surveys and Tutorials, 22(2), 1251\u20131275.","journal-title":"IEEE Communications Surveys and Tutorials"},{"key":"11680_CR11","doi-asserted-by":"publisher","first-page":"104234","DOI":"10.1016\/j.engappai.2021.104234","volume":"102","author":"M Abbasi","year":"2021","unstructured":"Abbasi, M., Shahraki, A., Jalil Piran, M., & Taherkordi, A. (2021). Deep reinforcement learning for QoS provisioning at the MAC layer: a survey. Engineering Applications of Artificial Intelligence, 102, 104234.","journal-title":"Engineering Applications of Artificial Intelligence"},{"issue":"10","key":"11680_CR12","doi-asserted-by":"publisher","first-page":"3718","DOI":"10.1109\/TMC.2021.3057826","volume":"21","author":"Y Yu","year":"2022","unstructured":"Yu, Y., Liew, S. C., & Wang, T. (2022). Multi-agent deep reinforcement learning multiple access for heterogeneous wireless networks with imperfect channels. IEEE Transactions on Mobile Computing, 21(10), 3718\u20133730. https:\/\/doi.org\/10.1109\/TMC.2021.3057826","journal-title":"IEEE Transactions on Mobile Computing"},{"key":"11680_CR13","doi-asserted-by":"crossref","unstructured":"Pei, G., & Chien, C., (2001) \"Low power TDMA in large wireless sensor networks,\" In 2001 MILCOM Proceedings Communications for Network-Centric Operations: Creating the Information Force (Cat. No.01CH37277), pp. 347\u2013351 vol.1.","DOI":"10.1109\/MILCOM.2001.985817"},{"key":"11680_CR14","doi-asserted-by":"publisher","unstructured":"Patidar, Y., Jain, M., & Vyas, A. K., (2022) \"Modified unexpended energy based stable cluster head selection for homogeneous wireless sensor networks (WSNs),\" In 2022 3rd International Conference on Computing, Analytics and Networks (ICAN), Rajpura, Punjab, India, pp. 1\u20135, https:\/\/doi.org\/10.1109\/ICAN56228.2022.10007098.","DOI":"10.1109\/ICAN56228.2022.10007098"},{"key":"11680_CR15","unstructured":"Patidar, Y., Jain, M., & Vyas, A. K., \u201cEnergy-efficient two layers hierarchal medium access control protocol for high density wireless sensor network,\u201d Unpublished."}],"container-title":["Wireless Personal Communications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11277-024-11680-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11277-024-11680-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11277-024-11680-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T16:07:46Z","timestamp":1734365266000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11277-024-11680-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11]]},"references-count":15,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2024,11]]}},"alternative-id":["11680"],"URL":"https:\/\/doi.org\/10.1007\/s11277-024-11680-5","relation":{},"ISSN":["0929-6212","1572-834X"],"issn-type":[{"value":"0929-6212","type":"print"},{"value":"1572-834X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11]]},"assertion":[{"value":"2 December 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 December 2024","order":2,"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 that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human\/animal participants performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human and animal participants"}}]}}