{"id":"https://openalex.org/W4408325634","doi":"https://doi.org/10.1109/globecom52923.2024.10901105","title":"Adaptive Federated Continual Learning for Heterogeneous Edge Environments: A Data-Free Distillation Approach","display_name":"Adaptive Federated Continual Learning for Heterogeneous Edge Environments: A Data-Free Distillation Approach","publication_year":2024,"publication_date":"2024-12-08","ids":{"openalex":"https://openalex.org/W4408325634","doi":"https://doi.org/10.1109/globecom52923.2024.10901105"},"language":"en","primary_location":{"id":"doi:10.1109/globecom52923.2024.10901105","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom52923.2024.10901105","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2024 - 2024 IEEE Global Communications Conference","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/A5067427510","display_name":"Bingqing Jiang","orcid":"https://orcid.org/0000-0002-3635-7779"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingqing Jiang","raw_affiliation_strings":["Tsinghua University,Department of Electronic Engineering,Beijing,China,100084"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Electronic Engineering,Beijing,China,100084","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033168204","display_name":"Jun Du","orcid":"https://orcid.org/0000-0002-5213-8808"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Du","raw_affiliation_strings":["Tsinghua University,Department of Electronic Engineering,Beijing,China,100084"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Electronic Engineering,Beijing,China,100084","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005072193","display_name":"Chunxiao Jiang","orcid":"https://orcid.org/0000-0002-3703-121X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunxiao Jiang","raw_affiliation_strings":["Tsinghua University,Beijing National Research Center for Information Science and Technology,Beijing,China,100084"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing National Research Center for Information Science and Technology,Beijing,China,100084","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101653399","display_name":"Ahmed Alhammadi","orcid":"https://orcid.org/0009-0006-8535-268X"},"institutions":[{"id":"https://openalex.org/I4210087059","display_name":"Technology Innovation Institute","ror":"https://ror.org/001kv2y39","country_code":"AE","type":"facility","lineage":["https://openalex.org/I4210087059"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Ahmed Alhammadi","raw_affiliation_strings":["Technology Innovation Institute,Abu Dhabi,UAE,9639"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technology Innovation Institute,Abu Dhabi,UAE,9639","institution_ids":["https://openalex.org/I4210087059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055773757","display_name":"Qiyang Zhao","orcid":"https://orcid.org/0000-0001-5420-2511"},"institutions":[{"id":"https://openalex.org/I4210087059","display_name":"Technology Innovation Institute","ror":"https://ror.org/001kv2y39","country_code":"AE","type":"facility","lineage":["https://openalex.org/I4210087059"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Qiyang Zhao","raw_affiliation_strings":["Technology Innovation Institute,Abu Dhabi,UAE,9639"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technology Innovation Institute,Abu Dhabi,UAE,9639","institution_ids":["https://openalex.org/I4210087059"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100660246","display_name":"Jintao Wang","orcid":"https://orcid.org/0000-0002-6162-4349"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jintao Wang","raw_affiliation_strings":["Tsinghua University,Department of Electronic Engineering,Beijing,China,100084"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Electronic Engineering,Beijing,China,100084","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4274","last_page":"4279"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9236999750137329,"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/T12676","display_name":"Machine Learning and ELM","score":0.9236999750137329,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9027000069618225,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7655009031295776},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.5941141843795776},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5633692741394043},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37373989820480347},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32606351375579834}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7655009031295776},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.5941141843795776},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5633692741394043},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37373989820480347},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32606351375579834},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom52923.2024.10901105","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom52923.2024.10901105","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2024 - 2024 IEEE Global Communications Conference","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/W2194775991","https://openalex.org/W2473930607","https://openalex.org/W3030364939","https://openalex.org/W3089283090","https://openalex.org/W4320005495","https://openalex.org/W4377079905","https://openalex.org/W4380303531","https://openalex.org/W4388820220","https://openalex.org/W4390874191","https://openalex.org/W4399665748","https://openalex.org/W6736334413","https://openalex.org/W6802617379","https://openalex.org/W6850300237","https://openalex.org/W6858617640"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Recently,":[0],"Federated":[1,49,124],"Learning":[2,51,126],"(FL)":[3],"has":[4],"revolutionized":[5],"the":[6,21,59,68,91,99,109,117,134,143,162,198,221,228],"processing":[7],"and":[8,98,105,170,187,217],"analysis":[9],"of":[10,13,28,61,86,167,191,200,212],"vast":[11],"volumes":[12],"data":[14,37,73,88,107,169,173,186,189,204,219,248],"generated":[15],"by":[16,183],"wireless":[17],"devices,":[18],"effectively":[19],"overcoming":[20],"traditional":[22],"cloud":[23],"computing":[24],"constraints":[25],"within":[26],"Internet":[27],"Things":[29],"(IoT)":[30],"networks.":[31],"However,":[32],"practical":[33],"challenges":[34],"arise":[35],"as":[36,48],"on":[38,71,76,103,202],"edge":[39],"devices":[40],"dynamically":[41],"changes,":[42],"necessitating":[43],"continuous":[44],"learning":[45],"capabilities":[46],"known":[47],"Continual":[50,125],"(FCL).":[52],"One":[53],"key":[54],"challenge":[55],"in":[56,129,139,245],"FCL":[57],"is":[58],"issue":[60],"catastrophic":[62],"forgetting,":[63],"which":[64,132,160],"refers":[65],"to":[66,89,164],"preserving":[67],"training":[69,75,110,182,222],"performance":[70],"old":[72,87,106,168,193,203,216],"while":[74,237],"new":[77,104,185,218],"data.":[78,194],"While":[79],"common":[80],"strategies":[81],"involve":[82],"retaining":[83],"a":[84,146,155],"subset":[85],"mitigate":[90],"issue,":[92],"privacy":[93],"concerns":[94],"limit":[95],"this":[96],"approach,":[97],"balance":[100],"between":[101],"emphasis":[102,213],"during":[108,220],"process":[111],"remains":[112],"inadequately":[113],"studied.":[114],"To":[115],"address":[116],"above":[118],"challenges,":[119],"we":[120,196],"propose":[121],"an":[122],"Adaptive":[123],"(AdapFCL)":[127],"method":[128,230],"heterogeneous":[130,247],"environment,":[131],"eliminates":[133],"need":[135],"for":[136,205,209,215],"episodic":[137],"memory":[138],"federated":[140],"settings.":[141],"Specifically,":[142],"server":[144,163],"employs":[145],"Deep":[147],"Convolutional":[148],"Generative":[149],"Adversarial":[150],"Network":[151],"(DCGAN)":[152],"model":[153],"with":[154,242],"data-free":[156],"knowledge":[157],"distillation":[158],"technique,":[159],"enables":[161],"learn":[165],"representations":[166],"generate":[171],"synthetic":[172,188],"involving":[174],"only":[175],"global":[176],"model.":[177],"Then":[178],"clients":[179],"perform":[180],"local":[181],"utilizing":[184],"instead":[190],"storing":[192],"Furthermore,":[195],"quantify":[197],"degree":[199],"forgetting":[201],"each":[206],"client,":[207],"allowing":[208],"adaptive":[210],"adjustment":[211],"weights":[214],"process.":[223],"Simulation":[224],"results":[225],"validate":[226],"that":[227],"proposed":[229],"can":[231],"achieve":[232],"superior":[233],"average":[234],"test":[235],"accuracy":[236],"maintaining":[238],"communication":[239],"efficiency":[240],"compared":[241],"baselines,":[243],"especially":[244],"highly":[246],"scenarios.":[249]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}