{"id":"https://openalex.org/W7139042231","doi":"https://doi.org/10.1109/globecom59602.2025.11431717","title":"Multi-Worker Selection based Distributed Swarm Learning for Edge IoT with Non-i.i.d. Data","display_name":"Multi-Worker Selection based Distributed Swarm Learning for Edge IoT with Non-i.i.d. Data","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7139042231","doi":"https://doi.org/10.1109/globecom59602.2025.11431717"},"language":null,"primary_location":{"id":"doi:10.1109/globecom59602.2025.11431717","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11431717","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 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/A5129873990","display_name":"Zhuoyu Yao","orcid":null},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhuoyu Yao","raw_affiliation_strings":["Georgia State University,Department of Computer Science,Atlanta,GA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia State University,Department of Computer Science,Atlanta,GA,USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100374822","display_name":"Yufei Wang","orcid":"https://orcid.org/0000-0002-2317-9010"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue Wang","raw_affiliation_strings":["Georgia State University,Department of Computer Science,Atlanta,GA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia State University,Department of Computer Science,Atlanta,GA,USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100747794","display_name":"Songyang Zhang","orcid":"https://orcid.org/0000-0003-4316-3320"},"institutions":[{"id":"https://openalex.org/I79516672","display_name":"University of Louisiana at Lafayette","ror":"https://ror.org/01x8rc503","country_code":"US","type":"education","lineage":["https://openalex.org/I2799628689","https://openalex.org/I79516672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Songyang Zhang","raw_affiliation_strings":["University of Louisiana,Department of Electrical and Computer Engineering,Lafayette,LA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Louisiana,Department of Electrical and Computer Engineering,Lafayette,LA,USA","institution_ids":["https://openalex.org/I79516672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129891120","display_name":"Yingshu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingshu Li","raw_affiliation_strings":["Georgia State University,Department of Computer Science,Atlanta,GA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia State University,Department of Computer Science,Atlanta,GA,USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130133996","display_name":"Zhipeng Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhipeng Cai","raw_affiliation_strings":["Georgia State University,Department of Computer Science,Atlanta,GA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia State University,Department of Computer Science,Atlanta,GA,USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073942971","display_name":"Zhi Tian","orcid":"https://orcid.org/0000-0002-2738-6826"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhi Tian","raw_affiliation_strings":["George Mason University,Department of Electrical and Computer Engineering,Fairfax,VA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"George Mason University,Department of Electrical and Computer Engineering,Fairfax,VA,USA","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1766","last_page":"1771"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.41909998655319214,"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"}},"topics":[{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.41909998655319214,"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"}},{"id":"https://openalex.org/T14413","display_name":"Advanced Technologies in Various Fields","score":0.09279999881982803,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.08829999715089798,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/selection","display_name":"Selection (genetic algorithm)","score":0.5741000175476074},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4864000082015991},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4855000078678131},{"id":"https://openalex.org/keywords/performance-metric","display_name":"Performance metric","score":0.4657999873161316},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.4544000029563904},{"id":"https://openalex.org/keywords/digital-subscriber-line","display_name":"Digital subscriber line","score":0.44679999351501465},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.35249999165534973},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.3481000065803528}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7821000218391418},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5741000175476074},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4864000082015991},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4855000078678131},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.4657999873161316},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.4544000029563904},{"id":"https://openalex.org/C201374245","wikidata":"https://www.wikidata.org/wiki/Q104534","display_name":"Digital subscriber line","level":2,"score":0.44679999351501465},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4320000112056732},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41130000352859497},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4016999900341034},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3831000030040741},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.35249999165534973},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.3312000036239624},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.3239000141620636},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.3174000084400177},{"id":"https://openalex.org/C158207573","wikidata":"https://www.wikidata.org/wiki/Q5747224","display_name":"Heterogeneous network","level":4,"score":0.31220000982284546},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.25920000672340393},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom59602.2025.11431717","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11431717","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8877980709075928,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"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":13,"referenced_works":["https://openalex.org/W2007339694","https://openalex.org/W2995022099","https://openalex.org/W3146812040","https://openalex.org/W3173670432","https://openalex.org/W4229029907","https://openalex.org/W4312871782","https://openalex.org/W4386469847","https://openalex.org/W4386702951","https://openalex.org/W4387870192","https://openalex.org/W4393371662","https://openalex.org/W4399728347","https://openalex.org/W4402157567","https://openalex.org/W4411447005"],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,125],"distributed":[3,35,113],"swarm":[4],"learning":[5,47],"(DSL)":[6],"offer":[7],"a":[8,39,99,138],"promising":[9],"paradigm":[10],"for":[11,42,104,167],"edge":[12,44],"Internet":[13],"of":[14,31,53,89,143,149,160,180],"Things.":[15],"Such":[16],"advancements":[17],"enhance":[18],"data":[19,37,64,83,144,193],"privacy,":[20],"communication":[21],"efficiency,":[22],"energy":[23],"saving,":[24],"and":[25,33,49,123,146,191,200],"model":[26,67,169],"scalability.":[27],"However,":[28],"the":[29,76,82,87,93,130,141,147,177,209],"presence":[30],"non-independent":[32],"identically":[34],"(non-i.i.d.)":[36],"pose":[38],"significant":[40],"challenge":[41],"multi-access":[43],"computing,":[45],"degrading":[46],"performance":[48,198],"diverging":[50],"training":[51,68],"behavior":[52,179],"vanilla":[54],"DSL.":[55],"Further,":[56],"there":[57],"still":[58],"lacks":[59],"theoretical":[60,174],"guidance":[61],"on":[62,176,187],"how":[63],"heterogeneity":[65,84,145],"affects":[66],"accuracy,":[69],"which":[70,109,136],"requires":[71],"thorough":[72],"investigation.":[73],"To":[74],"fill":[75],"gap,":[77],"this":[78,126,153],"paper":[79],"first":[80],"study":[81],"by":[85,184,205],"measuring":[86],"impact":[88],"non-i.i.d.":[90,118,192],"datasets":[91,190],"under":[92],"DSL":[94,150],"framework.":[95],"This":[96],"then":[97],"motivates":[98],"new":[100,117],"multi-worker":[101],"selection":[102,159],"design":[103],"DSL,":[105],"termed":[106],"M-DSL":[107,156,207],"algorithm,":[108],"works":[110,162],"effectively":[111],"with":[112],"heterogeneous":[114,189],"data.":[115],"A":[116],"degree":[119],"metric":[120],"is":[121],"introduced":[122],"defined":[124],"work":[127],"to":[128],"formulate":[129],"statistical":[131],"difference":[132],"among":[133],"local":[134],"datasets,":[135],"builds":[137],"connection":[139],"between":[140],"measure":[142],"evaluation":[148],"performance.":[151],"In":[152],"way,":[154],"our":[155,181,206],"guides":[157],"effective":[158],"multiple":[161],"who":[163],"make":[164],"prominent":[165],"contributions":[166],"global":[168],"updates.":[170],"We":[171],"also":[172],"provide":[173],"analysis":[175],"convergence":[178],"M-DSL,":[182],"followed":[183],"extensive":[185],"experiments":[186],"different":[188],"settings.":[194],"Numerical":[195],"results":[196],"verify":[197],"improvement":[199],"network":[201],"intelligence":[202],"enhancement":[203],"provided":[204],"beyond":[208],"benchmarks.":[210]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-20T00:00:00"}