{"id":"https://openalex.org/W4409474012","doi":"https://doi.org/10.1109/tnnls.2025.3552406","title":"Route-and-Aggregate Decentralized Federated Learning Under Communication Errors","display_name":"Route-and-Aggregate Decentralized Federated Learning Under Communication Errors","publication_year":2025,"publication_date":"2025-04-15","ids":{"openalex":"https://openalex.org/W4409474012","doi":"https://doi.org/10.1109/tnnls.2025.3552406","pmid":"https://pubmed.ncbi.nlm.nih.gov/40232929"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3552406","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3552406","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5044162704","display_name":"Weicai Li","orcid":"https://orcid.org/0000-0001-5119-8844"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weicai Li","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5119-8844","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086282554","display_name":"Tiejun Lv","orcid":"https://orcid.org/0000-0003-4127-2419"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiejun Lv","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4127-2419","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101544825","display_name":"Wei Ni","orcid":"https://orcid.org/0000-0002-4933-594X"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Wei Ni","raw_affiliation_strings":["School of Electrical and Data Engineering, University of Technology Sydney, Ultimo, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0002-4933-594X","affiliations":[{"raw_affiliation_string":"School of Electrical and Data Engineering, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102777906","display_name":"Jingbo Zhao","orcid":"https://orcid.org/0000-0002-4059-0864"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingbo Zhao","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4059-0864","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089270885","display_name":"Ekram Hossain","orcid":"https://orcid.org/0000-0002-5932-6887"},"institutions":[{"id":"https://openalex.org/I46247651","display_name":"University of Manitoba","ror":"https://ror.org/02gfys938","country_code":"CA","type":"education","lineage":["https://openalex.org/I46247651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ekram Hossain","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB, Canada"],"raw_orcid":"https://orcid.org/0000-0002-5932-6887","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB, Canada","institution_ids":["https://openalex.org/I46247651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042307561","display_name":"H. Vincent Poor","orcid":"https://orcid.org/0000-0002-2062-131X"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"H. Vincent Poor","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ, USA"],"raw_orcid":"https://orcid.org/0000-0002-2062-131X","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ, USA","institution_ids":["https://openalex.org/I20089843"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.1841,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.97007629,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"36","issue":"9","first_page":"16675","last_page":"16691"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9995999932289124,"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":0.9995999932289124,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9799000024795532,"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/T10796","display_name":"Cooperative Communication and Network Coding","score":0.9592999815940857,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/aggregate","display_name":"Aggregate (composite)","score":0.7615072727203369},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.6623840928077698},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49805378913879395},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.19385847449302673}],"concepts":[{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.7615072727203369},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.6623840928077698},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49805378913879395},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.19385847449302673},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3552406","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3552406","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:40232929","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40232929","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.49000000953674316,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G2627887285","display_name":null,"funder_award_id":"L222046","funder_id":"https://openalex.org/F4320334977","funder_display_name":"Beijing Municipal Natural Science Foundation"},{"id":"https://openalex.org/G481716612","display_name":null,"funder_award_id":"ECCS-2335876","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5003439219","display_name":null,"funder_award_id":"62271068","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334977","display_name":"Beijing Municipal Natural Science Foundation","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W595252221","https://openalex.org/W630423399","https://openalex.org/W2007572995","https://openalex.org/W2031684115","https://openalex.org/W2074796812","https://openalex.org/W2117905067","https://openalex.org/W2152453230","https://openalex.org/W2172852798","https://openalex.org/W2194775991","https://openalex.org/W2889939668","https://openalex.org/W2975156709","https://openalex.org/W2996845627","https://openalex.org/W3092012490","https://openalex.org/W3111419317","https://openalex.org/W3111919937","https://openalex.org/W3147822227","https://openalex.org/W3163739719","https://openalex.org/W3192649393","https://openalex.org/W3194291390","https://openalex.org/W3199788090","https://openalex.org/W3204183032","https://openalex.org/W3207184289","https://openalex.org/W3213143123","https://openalex.org/W4200234277","https://openalex.org/W4214916569","https://openalex.org/W4250589301","https://openalex.org/W4285304498","https://openalex.org/W4313387429","https://openalex.org/W4319338887","https://openalex.org/W4319865686","https://openalex.org/W4327643804","https://openalex.org/W4376464532","https://openalex.org/W4377141523","https://openalex.org/W4385338695","https://openalex.org/W4386073909","https://openalex.org/W4388854885","https://openalex.org/W4395064458"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4298221930","https://openalex.org/W2390279801","https://openalex.org/W2777914285","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W3176937389","https://openalex.org/W4408069290"],"abstract_inverted_index":{"Decentralized":[0],"federated":[1,178],"learning":[2,8,179],"(D-FL)":[3],"allows":[4],"clients":[5,48],"to":[6,59,67,105,202],"aggregate":[7],"models":[9,50],"locally,":[10],"offering":[11],"flexibility":[12],"and":[13,61,76,118,127,148,154],"scalability.":[14],"Existing":[15],"D-FL":[16,32,40,84,130,134,153,161,168],"methods":[17],"use":[18],"gossip":[19],"protocols,":[20],"which":[21],"are":[22,31,103],"inefficient":[23],"when":[24,92],"not":[25,194],"all":[26],"nodes":[27,189,191],"in":[28,136,143,196],"the":[29,80,95,132,163,175,185,197],"network":[30],"clients.":[33],"This":[34],"article":[35],"puts":[36],"forth":[37],"a":[38],"new":[39],"strategy,":[41],"termed":[42],"route-and-aggregate":[43],"(R&A)":[44],"D-FL,":[45],"where":[46],"participating":[47],"exchange":[49],"with":[51,94,159,169],"their":[52,64],"peers":[53],"through":[54,113],"established":[55],"routes":[56,93],"(as":[57],"opposed":[58],"flooding)":[60],"adaptively":[62],"normalize":[63],"aggregation":[65],"coefficients":[66],"compensate":[68],"for":[69],"communication":[70,170,182],"errors.":[71],"The":[72],"impact":[73],"of":[74,82,138,166,174,187,199],"routing":[75,188],"imperfect":[77],"links":[78],"on":[79],"convergence":[81,89],"R&A":[83,129,167],"is":[85,90,110],"analyzed,":[86],"revealing":[87],"that":[88,173,192],"minimized":[91],"minimum":[96],"end-to-end":[97],"(E2E)":[98],"packet":[99],"error":[100],"rates":[101],"(PERs)":[102],"employed":[104],"deliver":[106],"models.":[107,128],"Our":[108],"analysis":[109],"experimentally":[111],"validated":[112],"three":[114],"image":[115],"classification":[116],"tasks":[117],"two":[119],"next-word":[120],"prediction":[121],"tasks,":[122],"utilizing":[123],"widely":[124],"recognized":[125],"datasets":[126],"outperforms":[131],"flooding-based":[133],"method":[135],"terms":[137],"training":[139,164,198],"accuracy":[140,165],"by":[141],"35%":[142],"our":[144],"tested":[145],"ten-client":[146],"network,":[147],"shows":[149],"strong":[150],"synergy":[151],"between":[152],"networking.":[155],"In":[156],"another":[157],"test":[158],"ten":[160],"clients,":[162],"errors":[171],"approaches":[172],"ideal":[176],"centralized":[177],"(C-FL)":[180],"without":[181],"errors,":[183],"as":[184],"number":[186],"(i.e.,":[190],"do":[193],"participate":[195],"D-FL)":[200],"rises":[201],"28.":[203]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-29T08:53:18.405633","created_date":"2025-10-10T00:00:00"}