{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:22:21Z","timestamp":1792786941979,"version":"4.5.0"},"reference-count":51,"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:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Research Foundation, Singapore and Infocomm Media Development Authority","id":[{"id":"https:\/\/ror.org\/05qha6z89","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Fundamental Research Funds for the Central Universities","award":["2022JBQY004"],"award-info":[{"award-number":["2022JBQY004"]}]},{"name":"National Natural Science Foundation of China","award":["U24B20117"],"award-info":[{"award-number":["U24B20117"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Netw. Sci. Eng."],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/tnse.2026.3725097","type":"journal-article","created":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T19:03:33Z","timestamp":1787079813000},"page":"11399-11415","source":"Crossref","is-referenced-by-count":0,"title":["Maximizing Accuracy-Per-Cost in Vehicular Federated Learning via Active Inference and Two-Stage Resource Optimization"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-9197-649X","authenticated-orcid":false,"given":"Xiangqing","family":"Su","sequence":"first","affiliation":[{"name":"Beijing Jiaotong University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0647-1009","authenticated-orcid":false,"given":"Yan","family":"Huo","sequence":"additional","affiliation":[{"name":"Beijing Jiaotong University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0814-3391","authenticated-orcid":false,"given":"Zihan","family":"Chen","sequence":"additional","affiliation":[{"name":"Singapore University of Technology and Design"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0404-6466","authenticated-orcid":false,"given":"Jian","family":"Mao","sequence":"additional","affiliation":[{"name":"Beihang University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3308-0759","authenticated-orcid":false,"given":"Xiaoxuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Beijing Jiaotong University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4037-3149","authenticated-orcid":false,"given":"Tony Q.S.","family":"Quek","sequence":"additional","affiliation":[{"name":"Singapore University of Technology and Design"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2024.3427324"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.52202\/075280-0382"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2025.3538096"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2023.3309376"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2024.3350050"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3324962"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3527448"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3506161"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2024.3355179"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.3037554"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2023.3262829"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3103715"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/IWCMC51323.2021.9498853"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1186\/s13638-025-02435-2"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2023.3325843"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TMLCN.2025.3534754"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2023.3345363"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2024.3459086"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2022.3188571"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2025.3568875"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2025.3554759"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3365477"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2025.3528969"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICC52391.2025.11160913"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/GLOBECOM52923.2024.10901843"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.005.2300481"},{"key":"ref27","first-page":"1081","article-title":"On the power of adaptive weighted aggregation in heterogeneous federated learning and beyond","volume-title":"Proc. 28th Int. Conf. Artif. Intell. Statist.","volume":"258","author":"Zeng","year":"2025"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2022.3183996"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ENERGYCON58629.2024.10488805"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3427132"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2025.3633255"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3155381"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2025.3574552"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3522130"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TCCN.2024.3510577"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3415661"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3379001"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/LWC.2025.3585344"},{"key":"ref39","first-page":"14039","article-title":"Achieving linear speedup in non-IID federated bilevel learning","volume-title":"Proc. 40th Int. Conf. Mach. Learn.","volume":"202","author":"Huang","year":"2023"},{"key":"ref40","article-title":"Federated learning based on dynamic regularization","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Acar","year":"2021"},{"key":"ref41","first-page":"5132","article-title":"Scaffold: Stochastic controlled averaging for federated learning","volume-title":"Proc. 37th Int. Conf. Mach. Learn. JMLR.org","author":"Karimireddy","year":"2020"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2022.3151806"},{"key":"ref43","article-title":"Reinforcement learning through active inference","volume-title":"Proc. ICLR Workshop Bridging AI Cognitive Sci.","author":"Tschantz","year":"2020"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref45","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"key":"ref46","article-title":"Fashion-MNIST: A novel image dataset for benchmarking machine learning algorithms","author":"Xiao","year":"2017"},{"key":"ref47","first-page":"4651","article-title":"Proximal policy optimization algorithms","volume-title":"Proc. 34th Int. Conf. Mach. Learn. PMLR","author":"Schulman","year":"2017"},{"key":"ref48","first-page":"1861","article-title":"Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor","volume-title":"Proc. 35th Int. Conf. Mach. Learn.","volume":"80","author":"Haarnoja","year":"2018"},{"key":"ref49","first-page":"19","article-title":"Oort: Efficient federated learning via guided participant selection","volume-title":"Proc. 15th USENIX Symp. Operating Syst. Des. Implementation","author":"Lai","year":"2021"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TCCN.2024.3457525"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2022.3163085"}],"container-title":["IEEE Transactions on Network Science and Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6488902\/11264281\/11657950.pdf?arnumber=11657950","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T16:14:31Z","timestamp":1790266471000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11657950\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":51,"URL":"https:\/\/doi.org\/10.1109\/tnse.2026.3725097","relation":{},"ISSN":["2327-4697"],"issn-type":[{"value":"2327-4697","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}