{"id":"https://openalex.org/W4411688700","doi":"https://doi.org/10.1109/eucnc/6gsummit63408.2025.11037111","title":"Optimizing Federated Learning on Non-IID Data with Clustering and Model Sharing","display_name":"Optimizing Federated Learning on Non-IID Data with Clustering and Model Sharing","publication_year":2025,"publication_date":"2025-06-03","ids":{"openalex":"https://openalex.org/W4411688700","doi":"https://doi.org/10.1109/eucnc/6gsummit63408.2025.11037111"},"language":"en","primary_location":{"id":"doi:10.1109/eucnc/6gsummit63408.2025.11037111","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eucnc/6gsummit63408.2025.11037111","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Qufei Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I71459812","display_name":"Beijing International Studies University","ror":"https://ror.org/058s1vf87","country_code":"CN","type":"education","lineage":["https://openalex.org/I71459812"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qufei Zhang","raw_affiliation_strings":["Beijing-Dublin International College, University College Dublin,China"],"affiliations":[{"raw_affiliation_string":"Beijing-Dublin International College, University College Dublin,China","institution_ids":["https://openalex.org/I71459812"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088681785","display_name":"Yunshuang Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunshuang Wang","raw_affiliation_strings":["Institute of Information Engineering, Chinese Academy of Sciences,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Institute of Information Engineering, Chinese Academy of Sciences,Beijing,China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049981833","display_name":"LI Geng-sheng","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gengsheng Li","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences,Laboratory of Brain Atlas and Brain-inspired Intelligence,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences,Laboratory of Brain Atlas and Brain-inspired Intelligence,Beijing,China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072460590","display_name":"Barry Cardiff","orcid":"https://orcid.org/0000-0003-1303-8115"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Barry Cardiff","raw_affiliation_strings":["School of Electrical and Electronic Engineering, University College Dublin,Ireland"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, University College Dublin,Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047428471","display_name":"Pasika Ranaweera","orcid":"https://orcid.org/0000-0002-4484-2002"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Pasika Ranaweera","raw_affiliation_strings":["School of Electrical and Electronic Engineering, University College Dublin,Ireland"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, University College Dublin,Ireland","institution_ids":["https://openalex.org/I100930933"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I71459812"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0709323,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"205","last_page":"210"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998000264167786,"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":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10237","display_name":"Cryptography and Data Security","score":0.9775999784469604,"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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9474999904632568,"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/computer-science","display_name":"Computer science","score":0.7762932181358337},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6904653310775757},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4668021500110626},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35498708486557007},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3251347839832306},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.18670538067817688}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7762932181358337},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6904653310775757},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4668021500110626},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35498708486557007},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3251347839832306},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.18670538067817688}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/eucnc/6gsummit63408.2025.11037111","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eucnc/6gsummit63408.2025.11037111","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1987971958","https://openalex.org/W2535838896","https://openalex.org/W3047304572","https://openalex.org/W3110435694","https://openalex.org/W3116546042","https://openalex.org/W3154335119","https://openalex.org/W3198500200","https://openalex.org/W4312634912","https://openalex.org/W4320067912","https://openalex.org/W6637373629","https://openalex.org/W6728757088","https://openalex.org/W6752029299","https://openalex.org/W6759238902","https://openalex.org/W6850203944"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"The":[0],"increased":[1],"amount":[2],"of":[3,13,75,92],"data":[4],"generated":[5],"by":[6,28,77,118],"edge":[7],"computing":[8],"has":[9],"necessitated":[10],"the":[11,73,90,110],"development":[12],"efficient":[14],"methods":[15,129],"to":[16,95,120,124],"leverage":[17],"this":[18],"vast":[19],"information.":[20],"Federated":[21],"Learning":[22],"(FL)":[23],"offers":[24],"a":[25,59],"promising":[26],"solution":[27],"enabling":[29],"distributed":[30],"model":[31,50,82,85],"training":[32],"while":[33],"preserving":[34],"privacy.":[35],"However,":[36],"FL":[37],"faces":[38],"challenges":[39],"with":[40,104],"NonIndependent":[41],"and":[42,52,87,127,133],"Identically":[43],"Distributed":[44],"(Non-IID)":[45],"data,":[46],"which":[47],"can":[48],"impact":[49],"accuracy":[51,117],"convergence.":[53],"To":[54],"address":[55],"this,":[56],"we":[57],"propose":[58],"three-stage":[60],"framework":[61],"that":[62],"effectively":[63,71],"trains":[64],"models":[65],"in":[66,138],"Non-IID":[67,76,102,139],"scenarios.":[68,140],"Our":[69],"approach":[70],"reduces":[72],"effect":[74],"classifying":[78],"IID":[79],"clients,":[80],"evaluating":[81],"performance":[83],"through":[84],"sharing,":[86],"dynamically":[88],"adjusting":[89],"weighting":[91],"each":[93],"client":[94,97,106],"perform":[96],"selection.":[98],"We":[99],"created":[100],"extreme":[101],"environments":[103],"diverse":[105],"representation.":[107],"Tested":[108],"on":[109],"CIFAR-10":[111],"dataset,":[112],"our":[113],"method":[114],"improves":[115],"maximum":[116],"up":[119],"3.03":[121],"%":[122],"compared":[123],"other":[125],"state-of-the-art":[126],"traditional":[128],"such":[130],"as":[131],"FedProx":[132],"FedAvg,":[134],"demonstrating":[135],"its":[136],"effectiveness":[137]},"counts_by_year":[],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}