{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:18:10Z","timestamp":1792786690502,"version":"4.5.0"},"reference-count":48,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Saudi Arabian Cultural Bureau and Qassim University, Saudi Arabia","id":[{"id":"https:\/\/ror.org\/044weyr28","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Engineering and Physical Sciences Research Council (EPSRC) and U.K. Department for Science, Innovation and Technology","award":["EP\/X040518\/1"],"award-info":[{"award-number":["EP\/X040518\/1"]}],"id":[{"id":"https:\/\/ror.org\/028z36n30","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Open J. Commun. Soc."],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/ojcoms.2026.3731681","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T19:20:51Z","timestamp":1788808851000},"page":"11410-11427","source":"Crossref","is-referenced-by-count":0,"title":["Dynamic Graph Neural Network for Real-Time Failure Prediction in Industrial IoT Networks"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8305-6357","authenticated-orcid":false,"given":"Rehab","family":"Alawadh","sequence":"first","affiliation":[{"name":"University of York","place":["York, U.K."],"department":["Department of Computer Science"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7943-9977","authenticated-orcid":false,"given":"Mostafa Rahmani","family":"Ghourtani","sequence":"additional","affiliation":[{"name":"University of York","place":["York, U.K."]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5508-8757","authenticated-orcid":false,"given":"Hamed","family":"Ahmadi","sequence":"additional","affiliation":[{"name":"University of York","place":["York, U.K."]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0169-0704","authenticated-orcid":false,"given":"Poonam","family":"Yadav","sequence":"additional","affiliation":[{"name":"University of York","place":["York, U.K."],"department":["Department of Computer Science"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3480110"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3695248"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICSA65012.2025.00033"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2025.111098"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3616864"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2025.130400"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2025.3613845"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2026.3681198"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.52953\/PYAF8065"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2023.108829"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2024.104054"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3273292"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3143148"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2025.3551875"},{"key":"ref15","first-page":"1","article-title":"Diffusion convolutional recurrent neural network: Data-driven traffic forecasting","volume-title":"Proc. 6th Int. Conf. Learn. Represent. (ICLR)","author":"Li"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-31594-x"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5984"},{"key":"ref18","article-title":"Temporal graph networks for deep learning on dynamic graphs","author":"Rossi","year":"2020","journal-title":"arXiv:2006.10637"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2025.3573163"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i20.35508"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v40i17.38510"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s11633-024-1510-8"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403049"},{"key":"ref24","article-title":"DropEdge: Towards deep graph convolutional networks on node classification","author":"Rong","year":"2019","journal-title":"arXiv:1907.10903"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49660.2025.10888672"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.5555\/3045390.3045502"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.3389\/fdata.2021.693869"},{"key":"ref28","volume-title":"Deep Learning","author":"Goodfellow","year":"2016"},{"key":"ref29","first-page":"1","article-title":"Graph attention networks","volume-title":"Proc. 6th Int. Conf. Learn. Representations (ICLR)","author":"Veli\u010dkovi\u0107"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1406.1078"},{"key":"ref31","volume-title":"Dgnn Dataset and Preprocessing Resources","author":"Alawadh","year":"2026"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1126\/science.286.5439.509"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3332507"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1002\/SERIES1345"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/5254.708428"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.29172\/7c2a6982-6d72-4cd8-bba6-2fccb06a7011"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-31594-x"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/505"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/264"},{"key":"ref41","first-page":"17804","article-title":"Adaptive graph convolutional recurrent network for traffic forecasting","volume-title":"Proc. NIPS","author":"Bai"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403118"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5477"},{"key":"ref44","article-title":"Discrete graph structure learning for forecasting multiple time series","author":"Shang","year":"2021","journal-title":"arXiv:2101.06861"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467330"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557702"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i4.25556"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3615160"}],"container-title":["IEEE Open Journal of the Communications Society"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/8782661\/11343983\/11683496.pdf?arnumber=11683496","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T17:13:31Z","timestamp":1790270011000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11683496\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":48,"URL":"https:\/\/doi.org\/10.1109\/ojcoms.2026.3731681","relation":{},"ISSN":["2644-125X"],"issn-type":[{"value":"2644-125X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}