{"id":"https://openalex.org/W4401164194","doi":"https://doi.org/10.1109/eit60633.2024.10609948","title":"Performance Analysis of a Hybrid Federated-Centralized Learning Framework","display_name":"Performance Analysis of a Hybrid Federated-Centralized Learning Framework","publication_year":2024,"publication_date":"2024-05-30","ids":{"openalex":"https://openalex.org/W4401164194","doi":"https://doi.org/10.1109/eit60633.2024.10609948"},"language":"en","primary_location":{"id":"doi:10.1109/eit60633.2024.10609948","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eit60633.2024.10609948","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Electro Information Technology (eIT)","raw_type":"proceedings-article"},"type":"conference-paper","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":"https://openalex.org/A5021879917","display_name":"Bifta Sama Bari","orcid":"https://orcid.org/0000-0001-6102-1823"},"institutions":[{"id":"https://openalex.org/I63920570","display_name":"Tennessee Technological University","ror":"https://ror.org/05drmrq39","country_code":"US","type":"education","lineage":["https://openalex.org/I63920570"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bifta Sama Bari","raw_affiliation_strings":["Tennessee Technological University,College of Engineering,Cookevile,TN,USA,38505"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tennessee Technological University,College of Engineering,Cookevile,TN,USA,38505","institution_ids":["https://openalex.org/I63920570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041321160","display_name":"Sheikh Ghafoor","orcid":"https://orcid.org/0000-0001-7175-1619"},"institutions":[{"id":"https://openalex.org/I63920570","display_name":"Tennessee Technological University","ror":"https://ror.org/05drmrq39","country_code":"US","type":"education","lineage":["https://openalex.org/I63920570"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sheikh Ghafoor","raw_affiliation_strings":["Tennessee Technological University,College of Engineering,Cookevile,TN,USA,38505"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tennessee Technological University,College of Engineering,Cookevile,TN,USA,38505","institution_ids":["https://openalex.org/I63920570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074738133","display_name":"Kumar Yelamarthi","orcid":"https://orcid.org/0000-0002-0072-3909"},"institutions":[{"id":"https://openalex.org/I63920570","display_name":"Tennessee Technological University","ror":"https://ror.org/05drmrq39","country_code":"US","type":"education","lineage":["https://openalex.org/I63920570"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kumar Yelamarthi","raw_affiliation_strings":["Tennessee Technological University,College of Engineering,Cookevile,TN,USA,38505"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tennessee Technological University,College of Engineering,Cookevile,TN,USA,38505","institution_ids":["https://openalex.org/I63920570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I63920570"],"apc_list":null,"apc_paid":null,"fwci":1.4224,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.83241137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9883999824523926,"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":0.9883999824523926,"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":0.7456863522529602},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.34119656682014465},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.3270843029022217}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7456863522529602},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.34119656682014465},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3270843029022217}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/eit60633.2024.10609948","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eit60633.2024.10609948","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Electro Information Technology (eIT)","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":16,"referenced_works":["https://openalex.org/W2802897269","https://openalex.org/W2807006176","https://openalex.org/W2907379776","https://openalex.org/W3021654819","https://openalex.org/W3043758338","https://openalex.org/W3101755493","https://openalex.org/W3148765418","https://openalex.org/W3196965143","https://openalex.org/W4225358669","https://openalex.org/W4285137770","https://openalex.org/W4306317349","https://openalex.org/W4312906660","https://openalex.org/W4319878686","https://openalex.org/W4386322339","https://openalex.org/W4390828296","https://openalex.org/W4390871639"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Centralized":[0,53],"Learning":[1,5,19,54],"(CL)":[2],"in":[3,44,130],"Machine":[4],"(ML)":[6],"raises":[7],"privacy":[8],"concerns":[9],"due":[10],"to":[11,26,57,118,127],"data":[12],"aggregation":[13],"on":[14,66,107],"a":[15,50],"central":[16],"server.":[17],"Federated":[18,52],"(FL)":[20],"addresses":[21],"this":[22],"by":[23],"allowing":[24],"clients":[25],"share":[27],"model":[28,56],"updates":[29],"instead":[30],"of":[31,38,73,96,144],"raw":[32],"data.":[33],"However,":[34],"the":[35,94],"varying":[36,97],"capabilities":[37],"edge":[39,131],"devices":[40],"hinder":[41],"FL's":[42],"effectiveness":[43],"real-world":[45],"scenarios.":[46],"This":[47,123],"work":[48],"proposes":[49],"Hybrid":[51],"(HFCL)":[55],"overcome":[58],"these":[59],"limitations.":[60,75],"HFCL":[61,81,102,112,145],"optimizes":[62],"task":[63],"distribution":[64],"based":[65],"individual":[67],"client":[68,99],"capabilities,":[69],"enabling":[70],"collaboration":[71],"regardless":[72],"resource":[74],"We":[76,92],"implement":[77],"CL,":[78],"FL,":[79],"and":[80,84,103],"using":[82],"MNIST":[83],"CIFAR-10":[85],"datasets":[86],"with":[87,134],"Convolutional":[88],"Neural":[89],"Networks":[90],"(CNNs).":[91],"analyze":[93],"impact":[95],"active/passive":[98],"ratios":[100],"within":[101,146],"different":[104],"learning":[105,115],"rates":[106],"accuracy.":[108],"Results":[109],"demonstrate":[110],"that":[111],"significantly":[113],"improves":[114],"performance":[116],"compared":[117],"pure":[119],"FL":[120],"or":[121],"CL.":[122],"highlights":[124],"its":[125],"potential":[126],"address":[128],"limitations":[129],"computing":[132],"environments":[133],"disparate":[135],"computational":[136],"resources.":[137],"Future":[138],"research":[139],"directions":[140],"include":[141],"further":[142],"exploration":[143],"edge-based":[147],"FL.":[148]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}