{"id":"https://openalex.org/W4403826771","doi":"https://doi.org/10.1109/jiot.2024.3487473","title":"Speed Up Federated Learning in Heterogeneous Environments: A Dynamic Tiering Approach","display_name":"Speed Up Federated Learning in Heterogeneous Environments: A Dynamic Tiering Approach","publication_year":2024,"publication_date":"2024-10-28","ids":{"openalex":"https://openalex.org/W4403826771","doi":"https://doi.org/10.1109/jiot.2024.3487473"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2024.3487473","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3487473","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-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":"https://openalex.org/A5103285917","display_name":"Seyed Mahmoud Sajjadi Mohammadabadi","orcid":"https://orcid.org/0009-0001-9629-9734"},"institutions":[{"id":"https://openalex.org/I134113660","display_name":"University of Nevada, Reno","ror":"https://ror.org/01keh0577","country_code":"US","type":"education","lineage":["https://openalex.org/I134113660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Seyed Mahmoud Sajjadi Mohammadabadi","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Nevada Reno, Reno, NV, USA"],"raw_orcid":"https://orcid.org/0009-0001-9629-9734","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Nevada Reno, Reno, NV, USA","institution_ids":["https://openalex.org/I134113660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033413087","display_name":"Syed Zawad","orcid":null},"institutions":[{"id":"https://openalex.org/I4210085935","display_name":"IBM Research - Almaden","ror":"https://ror.org/005w8dd04","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210085935","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Syed Zawad","raw_affiliation_strings":["Research Department, IBM Research-Almaden, San Jose, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Department, IBM Research-Almaden, San Jose, CA, USA","institution_ids":["https://openalex.org/I4210085935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100524024","display_name":"Feng Yan","orcid":"https://orcid.org/0009-0004-6267-9423"},"institutions":[{"id":"https://openalex.org/I44461941","display_name":"University of Houston","ror":"https://ror.org/048sx0r50","country_code":"US","type":"education","lineage":["https://openalex.org/I44461941"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feng Yan","raw_affiliation_strings":["Computer Science Department and the Electrical and Computer Engineering Department, University of Houston, Houston, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department and the Electrical and Computer Engineering Department, University of Houston, Houston, TX, USA","institution_ids":["https://openalex.org/I44461941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072565301","display_name":"Lei Yang","orcid":"https://orcid.org/0000-0002-5176-003X"},"institutions":[{"id":"https://openalex.org/I134113660","display_name":"University of Nevada, Reno","ror":"https://ror.org/01keh0577","country_code":"US","type":"education","lineage":["https://openalex.org/I134113660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lei Yang","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Nevada Reno, Reno, NV, USA"],"raw_orcid":"https://orcid.org/0000-0002-5176-003X","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Nevada Reno, Reno, NV, USA","institution_ids":["https://openalex.org/I134113660"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.6077,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.98132458,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"12","issue":"5","first_page":"5026","last_page":"5035"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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":1.0,"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":0.9994000196456909,"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":0.9987999796867371,"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":0.8473193049430847},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4565635621547699},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3562585413455963},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3525894284248352}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8473193049430847},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4565635621547699},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3562585413455963},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3525894284248352}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2024.3487473","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3487473","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G224838894","display_name":null,"funder_award_id":"CAREER-2305491","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7475177059","display_name":null,"funder_award_id":"OIA-2148788","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2473418344","https://openalex.org/W2794825826","https://openalex.org/W2896457183","https://openalex.org/W2900182564","https://openalex.org/W2911586496","https://openalex.org/W2963179579","https://openalex.org/W2963209930","https://openalex.org/W2963952467","https://openalex.org/W2995022099","https://openalex.org/W3018102029","https://openalex.org/W3037871107","https://openalex.org/W3044211235","https://openalex.org/W3102785203","https://openalex.org/W3110773422","https://openalex.org/W3118608800","https://openalex.org/W3129519326","https://openalex.org/W3154608090","https://openalex.org/W3175192640","https://openalex.org/W3177170788","https://openalex.org/W3208693455","https://openalex.org/W4214607237","https://openalex.org/W4287332481","https://openalex.org/W4289147229","https://openalex.org/W4289147263","https://openalex.org/W4299283926","https://openalex.org/W4307823718","https://openalex.org/W4312810014","https://openalex.org/W4313643873","https://openalex.org/W4318812474","https://openalex.org/W4319778953","https://openalex.org/W4323519261","https://openalex.org/W4378697396","https://openalex.org/W4378718090","https://openalex.org/W4386075204","https://openalex.org/W4386131770","https://openalex.org/W4386280917","https://openalex.org/W4394639701","https://openalex.org/W4394924926","https://openalex.org/W6728757088","https://openalex.org/W6750269818","https://openalex.org/W6752191696","https://openalex.org/W6755174528","https://openalex.org/W6755207826","https://openalex.org/W6756436328","https://openalex.org/W6756756286","https://openalex.org/W6759063983","https://openalex.org/W6759226220","https://openalex.org/W6759238902","https://openalex.org/W6764838729","https://openalex.org/W6765541894","https://openalex.org/W6768511045","https://openalex.org/W6772307254","https://openalex.org/W6773817997","https://openalex.org/W6773976177","https://openalex.org/W6781232731","https://openalex.org/W6781318954","https://openalex.org/W6784239669","https://openalex.org/W6787148940","https://openalex.org/W6853386148"],"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":{"Federated":[0],"learning":[1,86],"(FL)":[2],"enables":[3,131],"collaborative":[4],"training":[5,12,38,50,56,172,181,201,219,274],"of":[6,20,39,52,60,96,121,174,212,228],"a":[7,74,160],"model":[8,99,124,283],"while":[9,280],"keeping":[10],"the":[11,36,49,84,97,101,122,136,146,155,170,199,209,235,273,282],"data":[13],"decentralized":[14],"and":[15,30,57,109,130,148,185,214,223,242,247],"private.":[16],"However,":[17],"in":[18,25,48,127,138,203],"Internet":[19],"Things":[21],"systems,":[22],"inherent":[23],"heterogeneity":[24,43,66],"processing":[26],"power,":[27],"communication":[28,149,183],"bandwidth,":[29],"task":[31],"size":[32],"can":[33,270],"significantly":[34,271],"hinder":[35],"efficient":[37],"large":[40,220],"models.":[41],"Such":[42],"would":[44],"render":[45],"vast":[46],"variations":[47],"time":[51,173,202,275],"clients,":[53],"lengthening":[54],"overall":[55,200],"wasting":[58],"resources":[59],"faster":[61],"clients.":[62],"To":[63],"tackle":[64],"these":[65],"challenges,":[67],"we":[68],"propose":[69],"dynamic":[70,161,189],"tiering-based":[71],"FL":[72,267],"(DTFL),":[73],"novel":[75],"system":[76],"that":[77,164,263],"leverages":[78],"distributed":[79],"optimization":[80],"principles":[81],"to":[82,100,125,134,168,194,197,232,278],"improve":[83],"edge":[85],"performance.":[87,258],"Based":[88],"on":[89,106,151,178],"clients\u2019":[90],"resources,":[91],"DTFL":[92,117,158,213,250,269],"dynamically":[93],"offloads":[94,118],"part":[95],"global":[98,123],"server,":[102],"alleviating":[103],"resource":[104],"constraints":[105],"slower":[107],"clients":[108,126,193,229],"speeding":[110],"up":[111,277],"training.":[112,142],"By":[113],"leveraging":[114],"split":[115],"learning,":[116],"different":[119,128],"portions":[120],"tiers":[129,196],"each":[132,175,204],"client":[133,176],"update":[135],"models":[137,221],"parallel":[139],"via":[140],"local-loss-based":[141],"This":[143],"helps":[144],"reduce":[145,272],"computation":[147],"demand":[150],"resource-constrained":[152],"devices,":[153],"mitigating":[154],"straggler":[156],"problem.":[157],"introduces":[159],"tier":[162,166,190],"scheduler":[163,191],"uses":[165],"profiling":[167],"estimate":[169],"expected":[171],"based":[177],"their":[179],"historical":[180],"time,":[182],"speed,":[184],"dataset":[186],"size.":[187],"The":[188],"assigns":[192],"suitable":[195],"minimize":[198],"round.":[205],"We":[206],"theoretically":[207],"prove":[208],"convergence":[210],"properties":[211],"validate":[215],"its":[216],"effectiveness":[217],"by":[218,276],"(ResNet-56":[222],"ResNet-110)":[224],"across":[225],"varying":[226],"numbers":[227],"(from":[230],"10":[231],"200)":[233],"using":[234],"popular":[236],"image":[237],"datasets":[238],"(CIFAR-10,":[239],"CIFAR-100,":[240],"CINIC-10,":[241],"HAM10000)":[243],"under":[244],"both":[245],"I.I.D":[246],"non-I.I.D":[248],"systems.":[249],"seamlessly":[251],"integrates":[252],"various":[253],"privacy":[254],"measures":[255],"without":[256],"sacrificing":[257],"Extensive":[259],"experimental":[260],"results":[261],"show":[262],"compared":[264],"with":[265],"state-of-the-art":[266],"methods,":[268],"80%":[279],"maintaining":[281],"accuracy.":[284]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}