{"id":"https://openalex.org/W4405021924","doi":"https://doi.org/10.26599/bdma.2024.9020029","title":"Large-Scale Model Meets Federated Learning: A Hierarchical Hybrid Distributed Training Mechanism for Intelligent Intersection Large-Scale Model","display_name":"Large-Scale Model Meets Federated Learning: A Hierarchical Hybrid Distributed Training Mechanism for Intelligent Intersection Large-Scale Model","publication_year":2024,"publication_date":"2024-12-01","ids":{"openalex":"https://openalex.org/W4405021924","doi":"https://doi.org/10.26599/bdma.2024.9020029"},"language":"en","primary_location":{"id":"doi:10.26599/bdma.2024.9020029","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2024.9020029","pdf_url":null,"source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.26599/bdma.2024.9020029","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115591728","display_name":"Chang Liu","orcid":"https://orcid.org/0000-0003-0650-1773"},"institutions":[{"id":"https://openalex.org/I4392021250","display_name":"State Key Laboratory of Networking and Switching Technology","ror":"https://ror.org/00qtv5q45","country_code":null,"type":"facility","lineage":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]},{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chang Liu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047467022","display_name":"Shaoyong Guo","orcid":"https://orcid.org/0000-0003-2033-8431"},"institutions":[{"id":"https://openalex.org/I4392021250","display_name":"State Key Laboratory of Networking and Switching Technology","ror":"https://ror.org/00qtv5q45","country_code":null,"type":"facility","lineage":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]},{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoyong Guo","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051247090","display_name":"Fangfang Dang","orcid":"https://orcid.org/0009-0007-8803-6735"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fangfang Dang","raw_affiliation_strings":["Network Security Center, State Grid Henan Electric Power Company Information Communication Branch,Zhengzhou,China,450052"],"affiliations":[{"raw_affiliation_string":"Network Security Center, State Grid Henan Electric Power Company Information Communication Branch,Zhengzhou,China,450052","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042944721","display_name":"Xuesong Qiu","orcid":"https://orcid.org/0000-0002-7899-539X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I4392021250","display_name":"State Key Laboratory of Networking and Switching Technology","ror":"https://ror.org/00qtv5q45","country_code":null,"type":"facility","lineage":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuesong Qiu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001378599","display_name":"Sujie Shao","orcid":"https://orcid.org/0000-0003-3945-0706"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I4392021250","display_name":"State Key Laboratory of Networking and Switching Technology","ror":"https://ror.org/00qtv5q45","country_code":null,"type":"facility","lineage":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sujie Shao","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5115591728"],"corresponding_institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4392021250"],"apc_list":null,"apc_paid":null,"fwci":1.808,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.87988161,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":"7","issue":"4","first_page":"1031","last_page":"1049"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9271000027656555,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9271000027656555,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.7689529657363892},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6990774869918823},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.6886287331581116},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5432880520820618},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.5328894853591919},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5162889361381531},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49849510192871094},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32864266633987427},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11586558818817139},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.05506414175033569},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.052959829568862915}],"concepts":[{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.7689529657363892},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6990774869918823},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6886287331581116},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5432880520820618},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.5328894853591919},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5162889361381531},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49849510192871094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32864266633987427},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11586558818817139},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.05506414175033569},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.052959829568862915},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.26599/bdma.2024.9020029","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2024.9020029","pdf_url":null,"source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:71f85ded888e4348be6e816df5c7c645","is_oa":true,"landing_page_url":"https://doaj.org/article/71f85ded888e4348be6e816df5c7c645","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Big Data Mining and Analytics, Vol 7, Iss 4, Pp 1031-1049 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.26599/bdma.2024.9020029","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2024.9020029","pdf_url":null,"source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2406220052","display_name":null,"funder_award_id":"62322103","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2405578611","https://openalex.org/W2949003697","https://openalex.org/W2962788286","https://openalex.org/W2978329087","https://openalex.org/W3017949972","https://openalex.org/W3033664100","https://openalex.org/W3037742216","https://openalex.org/W3045638580","https://openalex.org/W3153347425","https://openalex.org/W3162286130","https://openalex.org/W3168867926","https://openalex.org/W3173909648","https://openalex.org/W4206333838","https://openalex.org/W4212807813","https://openalex.org/W4285217780","https://openalex.org/W4312768957","https://openalex.org/W4312939270","https://openalex.org/W4361866125","https://openalex.org/W4366850747","https://openalex.org/W4385307867","https://openalex.org/W4385436503","https://openalex.org/W4386249632","https://openalex.org/W4386914180","https://openalex.org/W4388208052","https://openalex.org/W4394862623","https://openalex.org/W4401386967","https://openalex.org/W6728757088","https://openalex.org/W6739901393","https://openalex.org/W6796581206","https://openalex.org/W6850820320","https://openalex.org/W6851950068","https://openalex.org/W6855469159"],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2997094352","https://openalex.org/W2382997850","https://openalex.org/W2348909947","https://openalex.org/W2390968135","https://openalex.org/W3216976533","https://openalex.org/W4292672442"],"abstract_inverted_index":{"The":[0,47,69],"large-scale":[1,6],"model":[2],"(LSM)":[3],"can":[4],"handle":[5],"data":[7,67],"and":[8,45,58,61,75,81,143],"complex":[9],"problems,":[10],"effectively":[11],"improving":[12],"the":[13,20,30,105,137,157,163,166,173,177,184,187],"intelligence":[14,74],"level":[15],"of":[16,56,66,71,139,165,186],"urban":[17],"intersections.":[18],"However,":[19],"traffic":[21],"conditions":[22],"at":[23],"intersections":[24],"are":[25],"becoming":[26],"increasingly":[27],"complex,":[28],"so":[29],"intelligent":[31,106],"intersection":[32,107],"LSMs":[33],"(I":[34],"<sup":[35,98,116],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[36,99,117],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[37,100,118],"LSMs)":[38],"also":[39],"need":[40],"to":[41,155],"be":[42],"continuously":[43],"learned":[44],"updated.":[46],"traditional":[48],"cloud-based":[49],"training":[50,94,123],"method":[51],"incurs":[52],"a":[53,64,90,128],"significant":[54],"amount":[55],"computational":[57],"storage":[59],"overhead,":[60],"there":[62],"is":[63],"risk":[65],"leakage.":[68],"combination":[70],"edge":[72],"artificial":[73],"federated":[76,131,141,145],"learning":[77,132,142],"provides":[78],"an":[79,114,150],"efficient":[80],"highly":[82],"privacy":[83],"protected":[84],"computing":[85],"mode.":[86],"Therefore,":[87],"we":[88,112,126,148,161],"propose":[89,127,149],"hierarchical":[91,120,129],"hybrid":[92,121,130],"distributed":[93,122],"mechanism":[95],"for":[96,109],"I":[97,115],"LSM.":[101],"Firstly,":[102],"relying":[103],"on":[104],"system":[108],"cloud-network-terminal":[110],"integration,":[111],"constructed":[113],"LSM":[119],"architecture.":[124],"Then,":[125],"(H2Fed)":[133],"algorithm":[134,154,175],"that":[135,172],"combines":[136],"advantages":[138],"centralized":[140],"decentralized":[144],"learning.":[146],"Further,":[147],"adaptive":[151],"compressed":[152],"sensing":[153],"reduce":[156],"communication":[158,178],"overhead.":[159],"Finally,":[160],"analyze":[162],"convergence":[164],"H2Fed":[167,174],"algorithm.":[168],"Experimental":[169],"results":[170],"show":[171],"reduces":[176],"overhead":[179],"by":[180],"21.6%":[181],"while":[182],"ensuring":[183],"accuracy":[185],"model.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
