{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,18]],"date-time":"2025-09-18T04:26:04Z","timestamp":1758169564698,"version":"3.44.0"},"reference-count":20,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2025,8,30]],"date-time":"2025-08-30T00:00:00Z","timestamp":1756512000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,8,30]],"date-time":"2025-08-30T00:00:00Z","timestamp":1756512000000},"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":["Cluster Comput"],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1007\/s10586-025-05231-1","type":"journal-article","created":{"date-parts":[[2025,8,30]],"date-time":"2025-08-30T10:52:17Z","timestamp":1756551137000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["LQE-DT: a machine learning approach to proactive link quality prediction in IoT networks"],"prefix":"10.1007","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8746-3029","authenticated-orcid":false,"given":"Safia","family":"Gul","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0063-0347","authenticated-orcid":false,"given":"Bilal Ahmad","family":"Malik","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8504-5061","authenticated-orcid":false,"given":"M. Tariq","family":"Banday","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9575-0714","authenticated-orcid":false,"given":"Zahrah","family":"Ayub","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,8,30]]},"reference":[{"key":"5231_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TCE.2024.3356195","volume":"PP","author":"M Shahid","year":"2024","unstructured":"Shahid, M., et al.: Link-Quality based Energy-Efficient routing protocol for WSN in IoT. IEEE Trans. Consum. Electron. PP, 1 (2024). https:\/\/doi.org\/10.1109\/TCE.2024.3356195","journal-title":"IEEE Trans. Consum. Electron."},{"issue":"2","key":"5231_CR2","doi-asserted-by":"publisher","first-page":"696","DOI":"10.1109\/COMST.2021.3053615","volume":"23","author":"G Cerar","year":"2021","unstructured":"Cerar, G., Yetgin, H., Mohorcic, M., Fortuna, C.: Machine learning for wireless link quality estimation: A survey. IEEE Commun. Surv. Tutorials. 23(2), 696\u2013728 (2021). https:\/\/doi.org\/10.1109\/COMST.2021.3053615","journal-title":"IEEE Commun. Surv. Tutorials"},{"key":"5231_CR3","doi-asserted-by":"publisher","unstructured":"Sindjoung, M.L.F., Velempini, M., Minet, P.: Combining learners to predict link quality in wireless IoT networks. MELECON 2022 - IEEE Mediterr. Electrotech Conf. Proc. 1177\u20131182 (2022). https:\/\/doi.org\/10.1109\/MELECON53508.2022.9843006","DOI":"10.1109\/MELECON53508.2022.9843006"},{"issue":"1","key":"5231_CR4","doi-asserted-by":"publisher","first-page":"426","DOI":"10.1109\/COMST.2019.2916177","volume":"22","author":"SK Sharma","year":"2020","unstructured":"Sharma, S.K., Wang, X.: Toward massive machine type communications in Ultra-Dense cellular IoT networks: Current issues and machine Learning-Assisted solutions. IEEE Commun. Surv. Tutorials. 22(1), 426\u2013471 (2020). https:\/\/doi.org\/10.1109\/COMST.2019.2916177","journal-title":"IEEE Commun. Surv. Tutorials"},{"key":"5231_CR5","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1007\/s12243-021-00835-1","volume":"77","author":"MLF Sindjoung","year":"2022","unstructured":"Sindjoung, M.L.F., Minet, P.: Estimating and predicting link quality in wireless IoT networks. Ann. Des. Telecommun Telecommun. 77, 5\u20136 (2022). https:\/\/doi.org\/10.1007\/s12243-021-00835-1","journal-title":"Ann. Des. Telecommun Telecommun"},{"key":"5231_CR6","doi-asserted-by":"publisher","unstructured":"Sindjoung, M.L.F., Minet, P.: Wireless Link Quality Prediction in IoT Networks, 8th Int. Conf. Perform. Eval. Model. Wired Wirel. Networks, PEMWN 2019, 2019, (2019). https:\/\/doi.org\/10.23919\/PEMWN47208.2019.8986920","DOI":"10.23919\/PEMWN47208.2019.8986920"},{"key":"5231_CR7","unstructured":"Santhosha Kamath, M.S.K., Aravinda Raman, J., Singh, S.: SDN-Based Multipath Data Offloading Scheme using Link SDN-Based Multipath Data Offloading Scheme using Link Quality Prediction for LTE and WiFi Networks, (2021)"},{"key":"5231_CR8","doi-asserted-by":"publisher","unstructured":"Sun, W., Lu, W., Li, Q., Chen, L., Mu, D., Yuan, X.: WNN-LQE: Wavelet-Neural-Network-Based Link Quality Estimation for Smart Grid WSNs, IEEE Access, vol. 5, no. July, pp. 12788\u201312797, (2017). https:\/\/doi.org\/10.1109\/ACCESS.2017.2723360","DOI":"10.1109\/ACCESS.2017.2723360"},{"key":"5231_CR9","doi-asserted-by":"publisher","unstructured":"Tangsunantham, N., Pirak, C.: Experimental performance analysis of Hardware-Based link quality Estimation modelling applied to smart grid communications. Energies. 16(11) (2023). https:\/\/doi.org\/10.3390\/en16114326","DOI":"10.3390\/en16114326"},{"issue":"1","key":"5231_CR10","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1007\/s00500-021-06443-4","volume":"26","author":"ASJ Charles","year":"2022","unstructured":"Charles, A.S.J., Kalavathi, P.: A reliable link quality-based RPL routing for internet of things. Soft Comput. 26(1), 123\u2013135 (2022). https:\/\/doi.org\/10.1007\/s00500-021-06443-4","journal-title":"Soft Comput."},{"issue":"1","key":"5231_CR11","doi-asserted-by":"publisher","first-page":"11378","DOI":"10.1109\/ACCESS.2021.3051169","volume":"9","author":"L Liu","year":"2021","unstructured":"Liu, L., Lv, H., Xu, J., Shu, J.: A link quality Estimation method based on improved weighted extreme learning machine. IEEE Access. 9(1), 11378\u201311392 (2021). https:\/\/doi.org\/10.1109\/ACCESS.2021.3051169","journal-title":"IEEE Access."},{"key":"5231_CR12","doi-asserted-by":"publisher","first-page":"117623","DOI":"10.1109\/ACCESS.2020.3004772","volume":"8","author":"S Manzoor","year":"2020","unstructured":"Manzoor, S., Chen, Z., Gao, Y., Hei, X., Cheng, W.: Towards QoS-Aware load balancing for High-Density software defined WiFi networks. IEEE Access. 8, 117623\u2013117638 (2020). https:\/\/doi.org\/10.1109\/ACCESS.2020.3004772","journal-title":"IEEE Access."},{"key":"5231_CR13","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1109\/FIT.2017.00044","volume":"2017\u2013Janua","author":"Z Chen","year":"2017","unstructured":"Chen, Z., Manzoor, S., Gao, Y., Hei, X.: Achieving load balancing in High-Density software defined WiFi networks. Proc. - 2017 Int. Conf. Front. Inf. Technol. FIT. 2017. 2017\u2013Janua, 206\u2013211 (2017). https:\/\/doi.org\/10.1109\/FIT.2017.00044","journal-title":"Proc. - 2017 Int. Conf. Front. Inf. Technol. FIT. 2017"},{"issue":"3","key":"5231_CR14","doi-asserted-by":"publisher","first-page":"1619","DOI":"10.1007\/s11277-024-11346-2","volume":"136","author":"A Maheshwari","year":"2024","unstructured":"Maheshwari, A., Panneerselvam, K.: Optimizing RPL for load balancing and congestion mitigation in IoT network. Wirel. Pers. Commun. 136(3), 1619\u20131636 (2024). https:\/\/doi.org\/10.1007\/s11277-024-11346-2","journal-title":"Wirel. Pers. Commun."},{"key":"5231_CR15","doi-asserted-by":"publisher","DOI":"10.1109\/ICC42927.2021.9500396","author":"C Boucetta","year":"2021","unstructured":"Boucetta, C., Nour, B., Cusin, A., Moungla, H.: QoS in IoT networks based on link quality prediction. IEEE Int. Conf. Commun. No Icc. (2021). https:\/\/doi.org\/10.1109\/ICC42927.2021.9500396","journal-title":"IEEE Int. Conf. Commun. No Icc"},{"key":"5231_CR16","doi-asserted-by":"crossref","unstructured":"Brun-laguna, K., et al.: Connectivity To cite this version: Moving Beyond Testbeds? Lessons (We) Learned about Connectivity,., (2019)","DOI":"10.1109\/MPRV.2018.2873847"},{"issue":"9","key":"5231_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10462-024-10862-8","volume":"57","author":"VK Chauhan","year":"2024","unstructured":"Chauhan, V.K., Zhou, J., Lu, P., Molaei, S., Clifton, D.A.: A brief review of Hypernetworks in deep learning. Artif. Intell. Rev. 57(9), 1\u201329 (2024). https:\/\/doi.org\/10.1007\/s10462-024-10862-8","journal-title":"Artif. Intell. Rev."},{"issue":"1","key":"5231_CR18","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1007\/s12559-023-10179-8","volume":"16","author":"V Hassija","year":"2024","unstructured":"Hassija, V., et al.: Interpreting Black-Box models: A review on explainable artificial intelligence. Cognit Comput. 16(1), 45\u201374 (2024). https:\/\/doi.org\/10.1007\/s12559-023-10179-8","journal-title":"Cognit Comput."},{"issue":"1","key":"5231_CR19","doi-asserted-by":"publisher","first-page":"742","DOI":"10.1109\/JIOT.2023.3286276","volume":"11","author":"F Daghero","year":"2024","unstructured":"Daghero, F., Burrello, A., MacIi, E., Montuschi, P., Poncino, M., Pagliari, D.J.: Dynamic decision tree ensembles for Energy-Efficient inference on IoT edge nodes. IEEE Internet Things J. 11(1), 742\u2013757 (2024). https:\/\/doi.org\/10.1109\/JIOT.2023.3286276","journal-title":"IEEE Internet Things J."},{"key":"5231_CR20","doi-asserted-by":"publisher","unstructured":"Li, J., Othman, M.S., Chen, H., Yusuf, L.M.: Optimizing IoT intrusion detection system: Feature selection versus Feature extraction in machine learning. J. Big Data. 11(1) (2024). https:\/\/doi.org\/10.1186\/s40537-024-00892-y","DOI":"10.1186\/s40537-024-00892-y"}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-025-05231-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-025-05231-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-025-05231-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T21:22:42Z","timestamp":1758144162000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-025-05231-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,30]]},"references-count":20,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2025,10]]}},"alternative-id":["5231"],"URL":"https:\/\/doi.org\/10.1007\/s10586-025-05231-1","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"type":"print","value":"1386-7857"},{"type":"electronic","value":"1573-7543"}],"subject":[],"published":{"date-parts":[[2025,8,30]]},"assertion":[{"value":"16 October 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 February 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 March 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 August 2025","order":4,"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"}}],"article-number":"576"}}