{"id":"https://openalex.org/W4388723284","doi":"https://doi.org/10.3390/s23229226","title":"An Optimization Method for Non-IID Federated Learning Based on Deep Reinforcement Learning","display_name":"An Optimization Method for Non-IID Federated Learning Based on Deep Reinforcement Learning","publication_year":2023,"publication_date":"2023-11-16","ids":{"openalex":"https://openalex.org/W4388723284","doi":"https://doi.org/10.3390/s23229226","pmid":"https://pubmed.ncbi.nlm.nih.gov/38005610"},"language":"en","primary_location":{"id":"doi:10.3390/s23229226","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23229226","pdf_url":"https://www.mdpi.com/1424-8220/23/22/9226/pdf?version=1700137971","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/22/9226/pdf?version=1700137971","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057450353","display_name":"Xutao Meng","orcid":"https://orcid.org/0009-0004-5431-5224"},"institutions":[{"id":"https://openalex.org/I4385474403","display_name":"Changchun University of Technology","ror":"https://ror.org/052pakb34","country_code":"CN","type":"education","lineage":["https://openalex.org/I4385474403"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xutao Meng","raw_affiliation_strings":["School of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China"],"raw_orcid":"https://orcid.org/0009-0004-5431-5224","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China","institution_ids":["https://openalex.org/I4385474403"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100735403","display_name":"Yong Li","orcid":"https://orcid.org/0000-0002-2907-9811"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4210134929","display_name":"Jilin Province Science and Technology Department","ror":"https://ror.org/049x38272","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210134929"]},{"id":"https://openalex.org/I4385474403","display_name":"Changchun University of Technology","ror":"https://ror.org/052pakb34","country_code":"CN","type":"education","lineage":["https://openalex.org/I4385474403"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yong Li","raw_affiliation_strings":["AI Research Institute, Changchun University of Technology, Changchun 130012, China","School of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China","School of Computer Science and Technology, Jilin University, Changchun 130012, China"],"raw_orcid":"https://orcid.org/0000-0002-2907-9811","affiliations":[{"raw_affiliation_string":"AI Research Institute, Changchun University of Technology, Changchun 130012, China","institution_ids":["https://openalex.org/I4385474403"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China","institution_ids":["https://openalex.org/I4385474403"]},{"raw_affiliation_string":"School of Computer Science and Technology, Jilin University, Changchun 130012, China","institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4210134929"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061888850","display_name":"Jianchao Lu","orcid":"https://orcid.org/0000-0003-0788-1448"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jianchao Lu","raw_affiliation_strings":["School of Computing, Macquarie University, Sydney, NSW 2109, Australia"],"raw_orcid":"https://orcid.org/0000-0003-0788-1448","affiliations":[{"raw_affiliation_string":"School of Computing, Macquarie University, Sydney, NSW 2109, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102580029","display_name":"Xianglin Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I4385474403","display_name":"Changchun University of Technology","ror":"https://ror.org/052pakb34","country_code":"CN","type":"education","lineage":["https://openalex.org/I4385474403"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianglin Ren","raw_affiliation_strings":["School of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China","institution_ids":["https://openalex.org/I4385474403"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100735403"],"corresponding_institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4210134929","https://openalex.org/I4385474403"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":1.1866,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.82815974,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"23","issue":"22","first_page":"9226","last_page":"9226"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9606999754905701,"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"}},{"id":"https://openalex.org/T13918","display_name":"Advanced Data and IoT Technologies","score":0.9537000060081482,"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":0.7584052085876465},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6675460934638977},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6221571564674377},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.570896565914154},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.5225217342376709},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.518307626247406},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.47341662645339966},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42309439182281494},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.17207768559455872},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0967170000076294}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7584052085876465},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6675460934638977},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6221571564674377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.570896565914154},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5225217342376709},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.518307626247406},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.47341662645339966},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42309439182281494},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.17207768559455872},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0967170000076294},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s23229226","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23229226","pdf_url":"https://www.mdpi.com/1424-8220/23/22/9226/pdf?version=1700137971","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:38005610","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38005610","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":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10675381","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10675381","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10675381/pdf/sensors-23-09226.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:8ba0053b117244f58f09f99ba7828f95","is_oa":true,"landing_page_url":"https://doaj.org/article/8ba0053b117244f58f09f99ba7828f95","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 23, Iss 22, p 9226 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/23/22/9226/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s23229226","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s23229226","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23229226","pdf_url":"https://www.mdpi.com/1424-8220/23/22/9226/pdf?version=1700137971","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5199999809265137,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388723284.pdf","grobid_xml":"https://content.openalex.org/works/W4388723284.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W2155968351","https://openalex.org/W2541884796","https://openalex.org/W3006555759","https://openalex.org/W3022231501","https://openalex.org/W3033161486","https://openalex.org/W3038022836","https://openalex.org/W3043723611","https://openalex.org/W3045747588","https://openalex.org/W3047304572","https://openalex.org/W3127190257","https://openalex.org/W3155912831","https://openalex.org/W3159080474","https://openalex.org/W3162171002","https://openalex.org/W3163105316","https://openalex.org/W3168213397","https://openalex.org/W3170752158","https://openalex.org/W3170790803","https://openalex.org/W3182158470","https://openalex.org/W3182186656","https://openalex.org/W3196371845","https://openalex.org/W3204874618","https://openalex.org/W4206298942","https://openalex.org/W4226101686","https://openalex.org/W4285242833","https://openalex.org/W4287332481","https://openalex.org/W4292387144","https://openalex.org/W4385338532","https://openalex.org/W4387760980","https://openalex.org/W4387969561","https://openalex.org/W6759238902","https://openalex.org/W6781318954","https://openalex.org/W7018377419"],"related_works":["https://openalex.org/W4362501864","https://openalex.org/W4306904969","https://openalex.org/W4380318855","https://openalex.org/W2138720691","https://openalex.org/W2031695474","https://openalex.org/W2586732548","https://openalex.org/W3049728571","https://openalex.org/W20361778","https://openalex.org/W2024136090","https://openalex.org/W4375867731"],"abstract_inverted_index":{"Federated":[0],"learning":[1,7,76],"(FL)":[2],"is":[3,30,41],"a":[4,11,68,108],"distributed":[5,35],"machine":[6],"paradigm":[8],"that":[9,175],"enables":[10],"large":[12],"number":[13,179],"of":[14,54,91,105,180],"clients":[15,29,106],"to":[16,56,100,111,138],"collaboratively":[17],"train":[18],"models":[19,147],"without":[20,191],"sharing":[21],"data.":[22],"However,":[23],"when":[24],"the":[25,37,44,51,85,92,98,102,121,153,178,187,193],"private":[26],"dataset":[27,110],"between":[28],"not":[31,61],"independent":[32],"and":[33,88,119,162,195],"identically":[34],"(non-IID),":[36],"local":[38,142],"training":[39,46],"objective":[40],"inconsistent":[42],"with":[43,135,166,186],"global":[45],"objective,":[47],"which":[48],"possibly":[49],"causes":[50],"convergence":[52,118],"speed":[53],"FL":[55,70,170],"slow":[57],"down,":[58],"or":[59],"even":[60],"converge.":[62],"In":[63,80,128],"this":[64],"paper,":[65],"we":[66,82,131],"design":[67],"novel":[69],"framework":[71],"based":[72],"on":[73,141,152],"deep":[74],"reinforcement":[75],"(DRL),":[77],"named":[78],"FedRLCS.":[79],"FedRLCS,":[81],"primarily":[83],"improved":[84],"greedy":[86],"strategy":[87],"action":[89],"space":[90],"double":[93],"DQN":[94],"(DDQN)":[95],"algorithm,":[96],"enabling":[97],"server":[99],"select":[101],"optimal":[103],"subset":[104],"from":[107],"non-IID":[109,140,169],"participate":[112],"in":[113,124],"training,":[114],"thereby":[115],"accelerating":[116],"model":[117],"reaching":[120],"target":[122,189],"accuracy":[123,190],"fewer":[125],"communication":[126,181],"epochs.":[127],"simulation":[129],"experiments,":[130],"partition":[132],"multiple":[133],"datasets":[134,155],"different":[136],"strategies":[137],"simulate":[139],"clients.":[143,200],"We":[144],"adopt":[145],"four":[146,154],"(LeNet-5,":[148],"MobileNetV2,":[149],"ResNet-18,":[150],"ResNet-34)":[151],"(CIFAR-10,":[156],"CIFAR-100,":[157],"NICO,":[158],"Tiny":[159],"ImageNet),":[160],"respectively,":[161],"conduct":[163],"comparative":[164],"experiments":[165],"five":[167],"state-of-the-art":[168],"methods.":[171],"Experimental":[172],"results":[173],"show":[174],"FedRLCS":[176],"reduces":[177],"rounds":[182],"required":[183],"by":[184],"10-70%":[185],"same":[188],"increasing":[192],"computation":[194],"storage":[196],"costs":[197],"for":[198],"all":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
