{"id":"https://openalex.org/W4387870897","doi":"https://doi.org/10.1109/icc45041.2023.10279597","title":"Is Partial Model Aggregation Energy-Efficient for Federated Learning Enabled Wireless Networks?","display_name":"Is Partial Model Aggregation Energy-Efficient for Federated Learning Enabled Wireless Networks?","publication_year":2023,"publication_date":"2023-05-28","ids":{"openalex":"https://openalex.org/W4387870897","doi":"https://doi.org/10.1109/icc45041.2023.10279597"},"language":"en","primary_location":{"id":"doi:10.1109/icc45041.2023.10279597","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45041.2023.10279597","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2023 - IEEE International Conference on Communications","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/A5090876459","display_name":"Zhixiong Chen","orcid":"https://orcid.org/0000-0003-4228-0023"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Zhixiong Chen","raw_affiliation_strings":["School of Electronic Engineering and Computer Science, Queen Mary University of London,London,U.K","School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering and Computer Science, Queen Mary University of London,London,U.K","institution_ids":["https://openalex.org/I166337079"]},{"raw_affiliation_string":"School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041458779","display_name":"Wenqiang Yi","orcid":"https://orcid.org/0000-0003-4732-5040"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Wenqiang Yi","raw_affiliation_strings":["School of Electronic Engineering and Computer Science, Queen Mary University of London,London,U.K","School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering and Computer Science, Queen Mary University of London,London,U.K","institution_ids":["https://openalex.org/I166337079"]},{"raw_affiliation_string":"School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002265731","display_name":"Arumugam Nallanathan","orcid":"https://orcid.org/0000-0001-8337-5884"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Arumugam Nallanathan","raw_affiliation_strings":["School of Electronic Engineering and Computer Science, Queen Mary University of London,London,U.K","School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering and Computer Science, Queen Mary University of London,London,U.K","institution_ids":["https://openalex.org/I166337079"]},{"raw_affiliation_string":"School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039289964","display_name":"Geoffrey Ye Li","orcid":"https://orcid.org/0000-0002-7894-2415"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Geoffrey Ye Li","raw_affiliation_strings":["Imperial College,Faculty of Engineering,Department of Electrical and Electronic Engineering,London,England","Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College, London, England"],"affiliations":[{"raw_affiliation_string":"Imperial College,Faculty of Engineering,Department of Electrical and Electronic Engineering,London,England","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College, London, England","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5090876459"],"corresponding_institution_ids":["https://openalex.org/I166337079"],"apc_list":null,"apc_paid":null,"fwci":0.5274,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.72551479,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"166","last_page":"171"},"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/T13553","display_name":"Age of Information Optimization","score":0.967199981212616,"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/T11458","display_name":"Advanced Wireless Communication Technologies","score":0.9661999940872192,"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":0.8267947435379028},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.6575006246566772},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6091992855072021},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.547010600566864},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.472025066614151},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.4681834280490875},{"id":"https://openalex.org/keywords/data-aggregator","display_name":"Data aggregator","score":0.4439876675605774},{"id":"https://openalex.org/keywords/bisection-method","display_name":"Bisection method","score":0.4425826370716095},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.43481844663619995},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.41106700897216797},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.41106122732162476},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2815539240837097},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2188369333744049},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.1515076458454132}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8267947435379028},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.6575006246566772},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6091992855072021},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.547010600566864},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.472025066614151},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.4681834280490875},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.4439876675605774},{"id":"https://openalex.org/C157544257","wikidata":"https://www.wikidata.org/wiki/Q866300","display_name":"Bisection method","level":2,"score":0.4425826370716095},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.43481844663619995},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.41106700897216797},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.41106122732162476},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2815539240837097},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2188369333744049},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.1515076458454132},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icc45041.2023.10279597","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45041.2023.10279597","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2023 - IEEE International Conference on Communications","raw_type":"proceedings-article"},{"id":"pmh:oai:qmro.qmul.ac.uk:123456789/98239","is_oa":false,"landing_page_url":"https://qmro.qmul.ac.uk/xmlui/handle/123456789/98239","pdf_url":null,"source":{"id":"https://openalex.org/S4306400530","display_name":"Queen Mary Research Online (Queen Mary University of London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I166337079","host_organization_name":"Queen Mary University of London","host_organization_lineage":["https://openalex.org/I166337079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.5199999809265137,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2137152139","https://openalex.org/W2145080587","https://openalex.org/W2163922914","https://openalex.org/W2397723600","https://openalex.org/W2976335444","https://openalex.org/W3012968339","https://openalex.org/W3089655738","https://openalex.org/W3090615085","https://openalex.org/W3093755649","https://openalex.org/W3192649393","https://openalex.org/W3210413319","https://openalex.org/W3210823865","https://openalex.org/W4300427714","https://openalex.org/W4318619660","https://openalex.org/W4361192893","https://openalex.org/W6728757088","https://openalex.org/W6738383168","https://openalex.org/W6768570320","https://openalex.org/W6774978782","https://openalex.org/W6791102956","https://openalex.org/W6803358175","https://openalex.org/W6803611007"],"related_works":["https://openalex.org/W2577097539","https://openalex.org/W2329494729","https://openalex.org/W2109940557","https://openalex.org/W2466832359","https://openalex.org/W2793666424","https://openalex.org/W1606060475","https://openalex.org/W857034687","https://openalex.org/W2093193679","https://openalex.org/W2149099995","https://openalex.org/W4361214895"],"abstract_inverted_index":{"This":[0,67],"work":[1],"aims":[2],"to":[3,58,71,134,147],"address":[4,72,148],"two":[5],"of":[6,46,122],"the":[7,15,20,43,54,73,78,87,95,110,117,125,136,143,149,156,161,169,173,188],"main":[8],"challenges":[9],"for":[10,50,65],"federated":[11],"learning":[12],"(FL),":[13],"i.e.,":[14],"limited":[16],"communication":[17,102,118],"resources":[18],"and":[19,76,101,119,141,172,179],"data":[21,74,89],"heterogeneity":[22,75],"across":[23],"devices.":[24],"To":[25],"this":[26],"end,":[27],"we":[28,85],"first":[29],"devise":[30],"a":[31,131],"novel":[32],"FL":[33],"framework":[34],"with":[35,168],"partial":[36],"model":[37],"aggregation":[38],"(PMA),":[39],"which":[40],"only":[41],"aggregates":[42],"lower":[44],"layers":[45,56],"neural":[47],"networks":[48],"responsible":[49],"feature":[51],"extraction":[52],"while":[53],"upper":[55],"corresponding":[57],"complex":[59],"pattern":[60],"recognition":[61],"remain":[62],"at":[63],"devices":[64],"personalization.":[66],"design":[68],"is":[69,114],"able":[70],"reduce":[77],"transmitted":[79],"information":[80],"in":[81],"wireless":[82],"channels.":[83],"Then,":[84],"maximize":[86],"scheduled":[88],"sample":[90],"volume":[91],"by":[92],"joint":[93,175],"optimizing":[94],"device":[96,151,177],"scheduling,":[97],"bandwidth":[98,138],"allocation,":[99],"computation":[100,120],"time":[103,112,197],"division.":[104],"Specifically,":[105],"our":[106],"analysis":[107],"reveals":[108],"that":[109,160],"optimal":[111,137,150],"division":[113],"achieved":[115],"when":[116],"parts":[121],"PMA-FL":[123,163],"have":[124],"same":[126],"power.":[127],"We":[128],"also":[129],"develop":[130],"bisection":[132],"method":[133],"solve":[135],"allocation":[139],"policy":[140],"use":[142],"set":[144],"expansion":[145],"algorithm":[146],"scheduling.":[152],"Experimental":[153],"results":[154],"on":[155],"CIFAR-10":[157],"dataset":[158],"show":[159],"proposed":[162,174],"improves":[164],"11.6%":[165],"accuracy":[166,186],"compared":[167],"state-of-art":[170],"benchmarks,":[171],"dynamic":[176],"scheduling":[178],"resource":[180],"optimization":[181],"approach":[182],"achieves":[183],"slightly":[184],"higher":[185],"than":[187],"considered":[189],"benchmarks":[190],"but":[191],"reduced":[192],"25%":[193],"energy":[194],"or":[195],"12.5%":[196],"budgets.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}