{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T04:45:38Z","timestamp":1782967538690,"version":"3.54.5"},"reference-count":51,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Sustain. Comput."],"published-print":{"date-parts":[[2025,5]]},"DOI":"10.1109\/tsusc.2024.3504242","type":"journal-article","created":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T19:22:37Z","timestamp":1732216957000},"page":"576-587","source":"Crossref","is-referenced-by-count":7,"title":["Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9370-5023","authenticated-orcid":false,"given":"Nikolaos","family":"Pavlidis","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3915-9628","authenticated-orcid":false,"given":"Vasileios","family":"Perifanis","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0486-7731","authenticated-orcid":false,"given":"Selim F.","family":"Yilmaz","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, Imperial College London, London, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3936-535X","authenticated-orcid":false,"given":"Francesc","family":"Wilhelmi","sequence":"additional","affiliation":[{"name":"Nokia Bell Labs, Stuttgart, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3872-5907","authenticated-orcid":false,"given":"Marco","family":"Miozzo","sequence":"additional","affiliation":[{"name":"Sustainable Artificial Intelligence, Centre Tecnològic de Telecomunicacions de Catalunya (CTTC\/CERCA), Barcelona, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3749-0165","authenticated-orcid":false,"given":"Pavlos S.","family":"Efraimidis","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4478-7955","authenticated-orcid":false,"given":"Remous-Aris","family":"Koutsiamanis","sequence":"additional","affiliation":[{"name":"Department of Automation, Production and Computer Sciences, IMT Atlantique, Inria, LS2N, Nantes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pavol","family":"Mulinka","sequence":"additional","affiliation":[{"name":"Sustainable Artificial Intelligence, Centre Tecnològic de Telecomunicacions de Catalunya (CTTC\/CERCA), Barcelona, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6756-0289","authenticated-orcid":false,"given":"Paolo","family":"Dini","sequence":"additional","affiliation":[{"name":"Sustainable Artificial Intelligence, Centre Tecnològic de Telecomunicacions de Catalunya (CTTC\/CERCA), Barcelona, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/2007116.2007148"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.2017.1700200"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2022.109329"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2014.2345663"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3054840"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3209582.3209606"},{"key":"ref7","article-title":"How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?","author":"Cho","year":"2015"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/GLOBECOM46510.2021.9685639"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/SPAWC51858.2021.9593102"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TSUSC.2019.2905900"},{"key":"ref11","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"McMahan"},{"key":"ref12","article-title":"Federated learning: Strategies for improving communication efficiency","author":"Kone\u010dny","year":"2016"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2023.109950"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2020.3028197"},{"key":"ref15","volume-title":"Time Series Analysis: Forecasting and Control","author":"Box","year":"1976"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.42.7.1082"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2010-343"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6638947"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/AVSS.2018.8639163"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/PIMRC.2018.8581000"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/SAHCN.2019.8824981"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/LWC.2018.2795605"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.10.013"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOMW.2019.8845132"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref26","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3124673"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/FMEC59375.2023.10306017"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2991401"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/IV48863.2021.9575211"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488883"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/LCOMM.2022.3167813"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2015.55"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2020.2975749"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-33377-4_21"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17263"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-020-00800-3"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2020.3020582"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/OJCOMS.2023.3274394"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref41","journal-title":"Technical Specification Group Radio Access Network; Physical layerprocedures (Release 9)"},{"key":"ref42","article-title":"Carbontracker: Tracking and predicting the carbon footprint of training deep learning models","author":"Anthony","year":"2020"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.17"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.2307\/2291267"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2004.1380925"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3444690"},{"key":"ref47","first-page":"7611","article-title":"Tackling the objective inconsistency problem in heterogeneous federated optimization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Wang"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58607-2_5"},{"key":"ref49","article-title":"Adaptive federated optimization","author":"Reddi","year":"2020"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TSUSC.2023.3341836"},{"key":"ref51","article-title":"Upgini - Automated data search & enrichment library","author":"Post","year":"2022"}],"container-title":["IEEE Transactions on Sustainable Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7274860\/11026059\/10759814.pdf?arnumber=10759814","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,6]],"date-time":"2025-06-06T04:14:47Z","timestamp":1749183287000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10759814\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5]]},"references-count":51,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tsusc.2024.3504242","relation":{},"ISSN":["2377-3782","2377-3790"],"issn-type":[{"value":"2377-3782","type":"electronic"},{"value":"2377-3790","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5]]}}}