{"id":"https://openalex.org/W7148497449","doi":"https://doi.org/10.1109/tnsm.2026.3680350","title":"Deep Reinforcement Learning-Based Cluster Selection for Network-Layer Performance Guarantee in Federated Learning","display_name":"Deep Reinforcement Learning-Based Cluster Selection for Network-Layer Performance Guarantee in Federated Learning","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7148497449","doi":"https://doi.org/10.1109/tnsm.2026.3680350"},"language":null,"primary_location":{"id":"doi:10.1109/tnsm.2026.3680350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnsm.2026.3680350","pdf_url":null,"source":{"id":"https://openalex.org/S173527311","display_name":"IEEE Transactions on Network and Service Management","issn_l":"1932-4537","issn":["1932-4537","2373-7379"],"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 Network and Service Management","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":null,"display_name":"Yuchen Wu","orcid":"https://orcid.org/0009-0000-6338-0301"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuchen Wu","raw_affiliation_strings":["School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu, China"],"raw_orcid":"https://orcid.org/0009-0000-6338-0301","affiliations":[{"raw_affiliation_string":"School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077098691","display_name":"Muyu Mei","orcid":"https://orcid.org/0000-0002-0725-8560"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Muyu Mei","raw_affiliation_strings":["School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0002-0725-8560","affiliations":[{"raw_affiliation_string":"School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Li Feng","orcid":"https://orcid.org/0000-0002-6404-1130"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Feng","raw_affiliation_strings":["School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0002-6404-1130","affiliations":[{"raw_affiliation_string":"School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiangtao Wang","orcid":"https://orcid.org/0000-0002-8603-6084"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangtao Wang","raw_affiliation_strings":["State Key Laboratory of Integrated Services Networks, School of Telecommunication Engineering, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-8603-6084","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Services Networks, School of Telecommunication Engineering, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132768585","display_name":"Chunhui Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I1284762954","display_name":"Zhejiang A & F University","ror":"https://ror.org/02vj4rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I1284762954"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunhui Feng","raw_affiliation_strings":["College of Information Science and Electronic Engineering, Zhejiang University, Zhejiang University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Electronic Engineering, Zhejiang University, Zhejiang University, China","institution_ids":["https://openalex.org/I1284762954","https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xu Bao","orcid":"https://orcid.org/0000-0003-0347-5709"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Bao","raw_affiliation_strings":["School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0003-0347-5709","affiliations":[{"raw_affiliation_string":"School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008727851","display_name":"Mingwu Yao","orcid":"https://orcid.org/0000-0001-7045-8656"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingwu Yao","raw_affiliation_strings":["State Key Laboratory of Integrated Services Networks, School of Telecommunication Engineering, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0001-7045-8656","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Services Networks, School of Telecommunication Engineering, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.40815249,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"23","issue":null,"first_page":"3766","last_page":"3779"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.5738000273704529,"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":0.5738000273704529,"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/T13918","display_name":"Advanced Data and IoT Technologies","score":0.08020000159740448,"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"}},{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.02449999935925007,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.6273999810218811},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5716999769210815},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.477400004863739},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.33970001339912415},{"id":"https://openalex.org/keywords/distributed-database","display_name":"Distributed database","score":0.3237000107765198},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.3077999949455261},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.2985000014305115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8762000203132629},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6273999810218811},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5716999769210815},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5249000191688538},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.4830000102519989},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.477400004863739},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.33970001339912415},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3343999981880188},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C2775973920","wikidata":"https://www.wikidata.org/wiki/Q3252726","display_name":"Selection algorithm","level":3,"score":0.2858000099658966},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C2776807809","wikidata":"https://www.wikidata.org/wiki/Q6510160","display_name":"Learning automata","level":3,"score":0.26460000872612},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25450000166893005},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tnsm.2026.3680350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnsm.2026.3680350","pdf_url":null,"source":{"id":"https://openalex.org/S173527311","display_name":"IEEE Transactions on Network and Service Management","issn_l":"1932-4537","issn":["1932-4537","2373-7379"],"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 Network and Service Management","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5467235061","display_name":null,"funder_award_id":"62401232","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5563162130","display_name":null,"funder_award_id":"62202208","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Federated":[0],"learning":[1],"(FL)":[2],"is":[3],"a":[4,19,124,165,175,221,230,266,290],"privacy-preserving":[5],"technique":[6],"that":[7,273],"enables":[8],"local":[9],"model":[10,83,130,171,286],"training":[11],"on":[12,105,149,198],"devices":[13,70],"without":[14],"raw":[15],"data":[16],"sharing.":[17],"However,":[18,85],"critical":[20,91,142],"challenge":[21],"in":[22,25,46,280],"FL":[23,54,150,214],"lies":[24],"the":[26,31,62,69,75,80,99,157,172,186,191,194,249,262,294],"communication":[27,76],"requirement":[28],"of":[29,82,101,160,251,282],"uploading":[30],"trained":[32,195],"models":[33],"to":[34,96,110,128,184,206,243,260],"servers,":[35],"which":[36,108,181],"can":[37],"be":[38],"hindered":[39],"by":[40],"interference":[41,104,137],"from":[42,68,89],"ambient":[43],"devices,":[44],"particularly":[45],"unreliable":[47],"wireless":[48],"environments.":[49],"To":[50,139],"address":[51,140],"this,":[52],"hierarchical":[53],"(HFL)":[55],"introduces":[56],"an":[57,255],"additional":[58],"intermediate":[59],"layer":[60],"where":[61],"edge":[63],"server":[64],"performs":[65],"work":[66,162],"aggregation":[67],"nearby,":[71],"aiming":[72],"at":[73],"reducing":[74],"load":[77],"and":[78,115,132,144,163,189,209,226,247,285],"improving":[79],"efficiency":[81,134,250],"training.":[84],"existing":[86],"approaches":[87],"suffer":[88],"two":[90],"limitations.":[92],"First,":[93],"they":[94,122],"fail":[95],"fully":[97],"quantify":[98],"impact":[100],"device":[102],"competition-induced":[103],"transmission":[106,133,287],"performance,":[107,151],"leads":[109],"unacceptably":[111],"high":[112],"upload":[113,118],"latency":[114],"low":[116],"success":[117],"probability":[119],"(SUP).":[120],"Second,":[121],"lack":[123],"targeted":[125,166],"optimization":[126,219],"strategy":[127],"balance":[129,207],"accuracy":[131,208,284],"under":[135],"dynamic":[136],"conditions.":[138],"these":[141,154],"limitations":[143],"mitigate":[145],"their":[146],"adverse":[147],"impacts":[148],"we":[152,169,201,253],"take":[153],"gaps":[155],"as":[156,174,220],"core":[158],"motivation":[159],"our":[161,274],"propose":[164,202],"solution.":[167],"Specifically,":[168],"first":[170],"network":[173],"two-layer":[176],"binomial":[177],"point":[178],"process":[179,224],"(BPP),":[180],"allows":[182],"us":[183],"analyze":[185],"network-layer":[187,245],"performance":[188,246],"calculate":[190],"SUP":[192],"for":[193],"model.":[196],"Based":[197],"this":[199,218],"model,":[200],"optimizing":[203],"cluster":[204,237],"selection":[205,238],"latency,":[210,288],"thereby":[211],"enhancing":[212],"overall":[213],"performance.":[215],"We":[216],"formulate":[217],"Markov":[222],"decision":[223],"(MDP)":[225],"solve":[227],"it":[228],"using":[229],"twin-delayed":[231],"deep":[232],"deterministic":[233],"policy":[234],"gradient":[235],"(TD3)-based":[236],"algorithm":[239,259,275],"(CS-TD3).":[240],"In":[241],"addition,":[242],"guarantee":[244],"enhance":[248],"HFL,":[252],"employ":[254],"experimental":[256,270],"exhaustive":[257],"search":[258],"find":[261],"best":[263],"solution":[264],"within":[265],"limited":[267],"range.":[268],"The":[269],"results":[271],"show":[272],"overperforms":[276],"other":[277,295],"commonly-used":[278],"algorithms":[279],"terms":[281],"HFL":[283],"achieving":[289],"10.95%":[291],"improvement":[292],"over":[293],"methods.":[296]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-04-03T00:00:00"}
