{"id":"https://openalex.org/W4413823300","doi":"https://doi.org/10.1109/icccn65249.2025.11133765","title":"Fed-LyAHP: A Client Selection Method for Federated Learning based on Analytic Hierarchy Process and Lyapunov Optimization in Mobile Edge","display_name":"Fed-LyAHP: A Client Selection Method for Federated Learning based on Analytic Hierarchy Process and Lyapunov Optimization in Mobile Edge","publication_year":2025,"publication_date":"2025-08-04","ids":{"openalex":"https://openalex.org/W4413823300","doi":"https://doi.org/10.1109/icccn65249.2025.11133765"},"language":"en","primary_location":{"id":"doi:10.1109/icccn65249.2025.11133765","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccn65249.2025.11133765","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 34th International Conference on Computer Communications and Networks (ICCCN)","raw_type":"proceedings-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/A5020873740","display_name":"Zhaohua Zheng","orcid":"https://orcid.org/0000-0003-1525-2342"},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhaohua Zheng","raw_affiliation_strings":["Hainan University,School of CyberSpace Security (School of Cryptology),Haikou,China,570228"],"affiliations":[{"raw_affiliation_string":"Hainan University,School of CyberSpace Security (School of Cryptology),Haikou,China,570228","institution_ids":["https://openalex.org/I20942203"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102666015","display_name":"Junhui Du","orcid":"https://orcid.org/0009-0004-2963-7897"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junhui Du","raw_affiliation_strings":["Tianjin University,Center for Applied Mathematics,Tianjin,China,300072"],"affiliations":[{"raw_affiliation_string":"Tianjin University,Center for Applied Mathematics,Tianjin,China,300072","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5020873740"],"corresponding_institution_ids":["https://openalex.org/I20942203"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13130743,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9868999719619751,"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":0.9868999719619751,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9706000089645386,"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/T10927","display_name":"Access Control and Trust","score":0.9569000005722046,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/analytic-hierarchy-process","display_name":"Analytic hierarchy process","score":0.7982171773910522},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.744880735874176},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.7215999364852905},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6568140983581543},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.6297343373298645},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5751448273658752},{"id":"https://openalex.org/keywords/lyapunov-function","display_name":"Lyapunov function","score":0.5274662971496582},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.45759329199790955},{"id":"https://openalex.org/keywords/industrial-engineering","display_name":"Industrial engineering","score":0.33095037937164307},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3253564238548279},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.2679409980773926},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15527772903442383},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1318129599094391},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.07964354753494263},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.05875316262245178}],"concepts":[{"id":"https://openalex.org/C87345402","wikidata":"https://www.wikidata.org/wiki/Q485202","display_name":"Analytic hierarchy process","level":2,"score":0.7982171773910522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.744880735874176},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.7215999364852905},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6568140983581543},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.6297343373298645},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5751448273658752},{"id":"https://openalex.org/C60640748","wikidata":"https://www.wikidata.org/wiki/Q2337858","display_name":"Lyapunov function","level":3,"score":0.5274662971496582},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.45759329199790955},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.33095037937164307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3253564238548279},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.2679409980773926},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15527772903442383},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1318129599094391},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.07964354753494263},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.05875316262245178},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccn65249.2025.11133765","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccn65249.2025.11133765","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 34th International Conference on Computer Communications and Networks (ICCCN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2007339694","https://openalex.org/W2137152139","https://openalex.org/W2798720628","https://openalex.org/W3092144916","https://openalex.org/W3095593352","https://openalex.org/W3109847748","https://openalex.org/W3111182214","https://openalex.org/W3123459983","https://openalex.org/W3209696639","https://openalex.org/W4210453208","https://openalex.org/W4224246411","https://openalex.org/W4226358703","https://openalex.org/W4281388212","https://openalex.org/W4281394240","https://openalex.org/W4287332481","https://openalex.org/W4400490058","https://openalex.org/W4403046204"],"related_works":["https://openalex.org/W4318028252","https://openalex.org/W4206658728","https://openalex.org/W2385683470","https://openalex.org/W2605508318","https://openalex.org/W3134416257","https://openalex.org/W2322155822","https://openalex.org/W1745582813","https://openalex.org/W2325384277","https://openalex.org/W2357152830","https://openalex.org/W4295762775"],"abstract_inverted_index":{"Federated":[0],"Learning":[1],"(FL)":[2],"is":[3,53,101,178],"a":[4,121,163],"distributed":[5,19,28,34,80,114],"machine":[6],"learning":[7],"paradigm":[8],"that":[9,176,203],"trains":[10],"global":[11,47,64,108,169],"model":[12,16,48,109,143,192],"parameters":[13,17],"by":[14,208,247],"aggregating":[15],"from":[18,88],"clients,":[20],"offering":[21],"good":[22],"privacy":[23],"protection":[24],"due":[25,32],"to":[26,33,43,55,60,112,158,180,232],"its":[27],"training":[29,49,95,146,190],"characteristics.":[30],"Additionally,":[31],"training,":[35],"the":[36,46,57,63,67,71,89,93,107,130,149,160,168,172,218,225,234,242],"heterogeneity":[37],"between":[38],"different":[39,200],"clients":[40,59,81,104],"can":[41,139,244],"lead":[42],"instability":[44],"in":[45,62,106,148,167,187,212],"process.":[50],"Therefore,":[51],"it":[52,100],"necessary":[54],"select":[56],"right":[58],"participate":[61],"training.":[65],"At":[66],"same":[68],"time,":[69,191],"since":[70],"local":[72],"computing":[73],"resources":[74],"and":[75,135,145,185,194],"battery":[76],"power":[77],"of":[78,86,91,97,162,189,214,224,227],"most":[79],"are":[82],"less":[83],"than":[84],"those":[85],"servers,":[87],"perspective":[90],"reducing":[92],"long-term":[94],"cost":[96],"each":[98],"client,":[99],"beneficial":[102],"for":[103],"participating":[105,166],"parameter":[110],"update":[111,170],"be":[113,245],"across":[115],"multiple":[116],"clients.":[117],"This":[118],"paper":[119],"proposes":[120],"new":[122],"FL":[123],"client":[124,150,165],"selection":[125,151],"method":[126],"(Fed-LyAHP)":[127],"based":[128],"on":[129,198],"Analytic":[131],"Hierarchy":[132],"Process":[133],"(AHP)":[134],"Lyapunov":[136],"optimization,":[137],"which":[138],"not":[140],"only":[141,222],"balance":[142],"accuracy":[144,220,243],"time":[147],"process,":[152],"but":[153],"also":[154],"introduce":[155],"virtual":[156],"queues":[157],"reduce":[159],"probability":[161],"single":[164],"all":[171],"time.":[173],"Experiments":[174,197],"show":[175,202],"Fed-LyAHP":[177,204],"superior":[179],"Greedy":[181],"methods,":[182],"RBCS":[183],"F":[184],"FedCS,":[186],"terms":[188,213],"accuracy,":[193],"queue":[195,215],"length.":[196,216],"two":[199],"datasets":[201],"outperforms":[205],"other":[206,228],"algorithms":[207,229],"at":[209,248],"least":[210,249],"10%":[211],"In":[217,237],"fixed":[219,240],"experiment,":[221],"70%":[223],"iterations":[226],"were":[230],"used":[231],"achieve":[233],"target":[235],"accuracy.":[236],"experiments":[238],"with":[239],"run-time,":[241],"improved":[246],"10%.":[250]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}