{"id":"https://openalex.org/W4403918241","doi":"https://doi.org/10.1109/tcss.2024.3481882","title":"A Blockchain-Empowered Multiaggregator Federated Learning Architecture in Edge Computing With Deep Reinforcement Learning Optimization","display_name":"A Blockchain-Empowered Multiaggregator Federated Learning Architecture in Edge Computing With Deep Reinforcement Learning Optimization","publication_year":2024,"publication_date":"2024-10-30","ids":{"openalex":"https://openalex.org/W4403918241","doi":"https://doi.org/10.1109/tcss.2024.3481882"},"language":"en","primary_location":{"id":"doi:10.1109/tcss.2024.3481882","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2024.3481882","pdf_url":null,"source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"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 Computational Social Systems","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/A5100375279","display_name":"Xiao Li","orcid":"https://orcid.org/0000-0002-2036-291X"},"institutions":[{"id":"https://openalex.org/I16269868","display_name":"Santa Clara University","ror":"https://ror.org/03ypqe447","country_code":"US","type":"education","lineage":["https://openalex.org/I16269868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiao Li","raw_affiliation_strings":["Department of Computer Science and Engineering, Santa Clara University, Santa Clara, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2036-291X","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Santa Clara University, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I16269868"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070037321","display_name":"Weili Wu","orcid":"https://orcid.org/0000-0001-8747-6340"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weili Wu","raw_affiliation_strings":["Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA"],"raw_orcid":"https://orcid.org/0000-0001-8747-6340","affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2150,"currency":"USD","value_usd":2150},"apc_paid":null,"fwci":0.6902,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.76423801,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":97},"biblio":{"volume":"12","issue":"2","first_page":"645","last_page":"657"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9986000061035156,"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":0.9986000061035156,"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/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9787999987602234,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9528999924659729,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/blockchain","display_name":"Blockchain","score":0.8470195531845093},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8414838314056396},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7295135259628296},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5892988443374634},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.5797966122627258},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5439576506614685},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.5381186604499817},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.490951806306839},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.45992976427078247},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45387640595436096},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4102594256401062},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3922174870967865},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.23498356342315674},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.14308112859725952}],"concepts":[{"id":"https://openalex.org/C2779687700","wikidata":"https://www.wikidata.org/wiki/Q20514253","display_name":"Blockchain","level":2,"score":0.8470195531845093},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8414838314056396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7295135259628296},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5892988443374634},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.5797966122627258},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5439576506614685},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.5381186604499817},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.490951806306839},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.45992976427078247},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45387640595436096},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4102594256401062},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3922174870967865},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.23498356342315674},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.14308112859725952},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcss.2024.3481882","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2024.3481882","pdf_url":null,"source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"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 Computational Social Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7784844501","display_name":"SPX: Collaborative Research: Enabling Efficient Computer Architectural and System Support for Next-Generation Network Function Virtualization","funder_award_id":"1822985","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7950295864","display_name":"III: Small: Collaborative Research: Stream-Based Active Mining at Scale: Non-Linear Non-Submodular Maximization","funder_award_id":"1907472","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W2914212774","https://openalex.org/W2951832089","https://openalex.org/W2974429275","https://openalex.org/W3006655855","https://openalex.org/W3009627224","https://openalex.org/W3014517104","https://openalex.org/W3047245989","https://openalex.org/W3048448986","https://openalex.org/W3111419317","https://openalex.org/W3122294042","https://openalex.org/W3126528290","https://openalex.org/W3128475867","https://openalex.org/W3131052410","https://openalex.org/W3156226702","https://openalex.org/W3158350046","https://openalex.org/W3186541329","https://openalex.org/W3194978182","https://openalex.org/W3212539584","https://openalex.org/W3212552055","https://openalex.org/W3215924452","https://openalex.org/W4200486839","https://openalex.org/W4206116305","https://openalex.org/W4206358929","https://openalex.org/W4206508980","https://openalex.org/W4210258335","https://openalex.org/W4226256841","https://openalex.org/W4283707608","https://openalex.org/W4285226023","https://openalex.org/W4286268436","https://openalex.org/W4294733424","https://openalex.org/W4307814244","https://openalex.org/W4307926598","https://openalex.org/W4307945509","https://openalex.org/W4310050331","https://openalex.org/W4323519324","https://openalex.org/W4381785392","https://openalex.org/W4382203046","https://openalex.org/W4382365365","https://openalex.org/W4382463479","https://openalex.org/W6678832241","https://openalex.org/W6684921986","https://openalex.org/W6728757088","https://openalex.org/W6743688258","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W4322761281","https://openalex.org/W4238233472","https://openalex.org/W3111395152","https://openalex.org/W4313526662","https://openalex.org/W4313463218","https://openalex.org/W3106131444","https://openalex.org/W3216099748","https://openalex.org/W4205963435","https://openalex.org/W4312996489","https://openalex.org/W3214037210"],"abstract_inverted_index":{"Federated":[0],"learning":[1,10,95,151],"(FL)":[2],"is":[3,79],"emerging":[4],"as":[5],"a":[6,66,100,147],"sought-after":[7],"distributed":[8],"machine":[9],"architecture,":[11],"offering":[12],"the":[13,38,50,69,83,90,121,127,158,167,179],"advantage":[14],"of":[15,71,134,169,181],"model":[16,113],"training":[17,143,160],"without":[18],"direct":[19],"exposure":[20],"to":[21,47,56,108,154,171],"raw":[22],"data.":[23],"With":[24],"advancements":[25],"in":[26,49,76,82,117,124],"network":[27],"infrastructure,":[28],"FL":[29,48,72],"has":[30],"been":[31],"seamlessly":[32],"integrated":[33],"into":[34],"edge":[35,42,63,77],"computing.":[36],"However,":[37],"limited":[39],"resources":[40],"on":[41,61,163],"devices":[43,64],"introduce":[44,89],"security":[45],"vulnerabilities":[46],"context.":[51],"While":[52],"blockchain":[53],"technology":[54],"promises":[55],"bolster":[57],"security,":[58],"practical":[59],"deployment":[60],"resource-constrained":[62],"remains":[65],"challenge.":[67],"Moreover,":[68],"exploration":[70],"with":[73,131,137],"multiple":[74],"aggregators":[75,128,156],"computing":[78],"still":[80],"new":[81],"literature.":[84],"Addressing":[85],"these":[86],"gaps,":[87],"we":[88],"blockchain-empowered":[91],"heterogeneous":[92],"multiaggregator":[93],"federated":[94],"architecture":[96],"(BMA-FL).":[97],"We":[98,119,145],"design":[99],"novel":[101],"lightweight":[102],"Byzantine":[103],"consensus":[104],"mechanism,":[105],"namely":[106],"PBCM,":[107],"enable":[109],"secure":[110],"and":[111,115,141,183],"fast":[112],"aggregation":[114],"synchronization":[116],"BMA-FL.":[118],"study":[120],"heterogeneity":[122],"problem":[123],"BMA-FL":[125,170],"that":[126],"are":[129],"associated":[130],"varied":[132],"number":[133],"connected":[135],"trainers":[136],"non-IID":[138],"data":[139],"distributions":[140],"diverse":[142],"speed.":[144],"propose":[146],"multiagent":[148],"deep":[149],"reinforcement":[150],"algorithm":[152],"(MASB-DRL)":[153],"help":[155],"decide":[157],"best":[159],"strategies.":[161],"Experiments":[162],"real-word":[164],"datasets":[165],"demonstrate":[166],"efficiency":[168],"achieve":[172],"better":[173],"models":[174],"faster":[175],"than":[176],"baselines,":[177],"showing":[178],"efficacy":[180],"PBCM":[182],"MASB-DRL.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}
