{"id":"https://openalex.org/W3138285433","doi":"https://doi.org/10.1109/ccnc49032.2021.9369497","title":"Efficient Parameter Aggregation in Federated Learning with Hybrid Convergecast","display_name":"Efficient Parameter Aggregation in Federated Learning with Hybrid Convergecast","publication_year":2021,"publication_date":"2021-01-09","ids":{"openalex":"https://openalex.org/W3138285433","doi":"https://doi.org/10.1109/ccnc49032.2021.9369497","mag":"3138285433"},"language":"en","primary_location":{"id":"doi:10.1109/ccnc49032.2021.9369497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccnc49032.2021.9369497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC)","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/A5026874272","display_name":"Yangyang Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yangyang Tao","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028358992","display_name":"Junxiu Zhou","orcid":"https://orcid.org/0000-0003-0067-1392"},"institutions":[{"id":"https://openalex.org/I168416876","display_name":"Northern Kentucky University","ror":"https://ror.org/01k44g025","country_code":"US","type":"education","lineage":["https://openalex.org/I168416876"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junxiu Zhou","raw_affiliation_strings":["Department of Computer Science, Northern Kentucky University, Highland Heights, KY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Northern Kentucky University, Highland Heights, KY, USA","institution_ids":["https://openalex.org/I168416876"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063617425","display_name":"Shucheng Yu","orcid":"https://orcid.org/0000-0001-6484-4382"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shucheng Yu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5026874272"],"corresponding_institution_ids":["https://openalex.org/I108468826"],"apc_list":null,"apc_paid":null,"fwci":0.5439,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.71342514,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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":1.0,"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":0.9890000224113464,"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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9797000288963318,"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/news-aggregator","display_name":"News aggregator","score":0.8702476024627686},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8122072219848633},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.665874719619751},{"id":"https://openalex.org/keywords/upload","display_name":"Upload","score":0.6473163366317749},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5985033512115479},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5952717661857605},{"id":"https://openalex.org/keywords/data-aggregator","display_name":"Data aggregator","score":0.4319475591182709},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3967287540435791},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34681928157806396},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34472107887268066},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.20984375476837158},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.12939807772636414}],"concepts":[{"id":"https://openalex.org/C180505990","wikidata":"https://www.wikidata.org/wiki/Q498267","display_name":"News aggregator","level":2,"score":0.8702476024627686},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8122072219848633},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.665874719619751},{"id":"https://openalex.org/C71901391","wikidata":"https://www.wikidata.org/wiki/Q7126699","display_name":"Upload","level":2,"score":0.6473163366317749},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5985033512115479},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5952717661857605},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.4319475591182709},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3967287540435791},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34681928157806396},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34472107887268066},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.20984375476837158},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.12939807772636414},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccnc49032.2021.9369497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccnc49032.2021.9369497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W564832898","https://openalex.org/W2001032894","https://openalex.org/W2053637704","https://openalex.org/W2114900869","https://openalex.org/W2116612304","https://openalex.org/W2132737349","https://openalex.org/W2336650964","https://openalex.org/W2535838896","https://openalex.org/W2566160073","https://openalex.org/W2611798620","https://openalex.org/W2798720628","https://openalex.org/W2807006176","https://openalex.org/W2809158980","https://openalex.org/W2809192003","https://openalex.org/W2886722183","https://openalex.org/W2900120080","https://openalex.org/W2913243576","https://openalex.org/W2945262235","https://openalex.org/W2949003697","https://openalex.org/W2953498285","https://openalex.org/W2962804345","https://openalex.org/W2963504849","https://openalex.org/W2975802305","https://openalex.org/W2996845627","https://openalex.org/W3038028469","https://openalex.org/W3103320149","https://openalex.org/W3105122387","https://openalex.org/W3106356772","https://openalex.org/W4235152108","https://openalex.org/W4292084264","https://openalex.org/W4297687186","https://openalex.org/W4300427714","https://openalex.org/W4318619660","https://openalex.org/W6663928093","https://openalex.org/W6679393576","https://openalex.org/W6703420464","https://openalex.org/W6728757088","https://openalex.org/W6738383168","https://openalex.org/W6752029299","https://openalex.org/W6753725573","https://openalex.org/W6755988804","https://openalex.org/W6758455886","https://openalex.org/W6759226220","https://openalex.org/W6762326562","https://openalex.org/W6764791836"],"related_works":["https://openalex.org/W3036238356","https://openalex.org/W2999291290","https://openalex.org/W2767445978","https://openalex.org/W2603387358","https://openalex.org/W4255106211","https://openalex.org/W2120644424","https://openalex.org/W2766329713","https://openalex.org/W2290626493","https://openalex.org/W3082121784","https://openalex.org/W2161995522"],"abstract_inverted_index":{"In":[0,30,100],"federated":[1,98,126],"learning,":[2],"workers":[3,39],"train":[4],"local":[5,15,138,150,160],"models":[6],"with":[7],"their":[8],"private":[9],"data":[10],"sets":[11],"and":[12,26,40,68,83,115,122,147],"only":[13],"upload":[14],"gradients":[16],"to":[17,43,93,119,140,142,162,165,189,204,221],"the":[18,41,58,63,69,72,85,95,163,167,173,176,198,206,212,222,225],"remote":[19],"aggregator.":[20],"Data":[21],"privacy":[22],"is":[23,28,157,202],"well":[24],"preserved":[25],"parallelism":[27],"achieved.":[29],"large-scale":[31],"deep":[32],"learning":[33],"tasks,":[34],"however,":[35],"frequent":[36],"interactions":[37],"between":[38],"aggregator":[42,164],"transmit":[44],"parameters":[45],"can":[46],"cause":[47],"tremendous":[48],"degradation":[49],"of":[50,55,61,65,71,76,97,175,184,208,224],"system":[51,77,185,217],"performance":[52,96],"in":[53,125,182],"terms":[54,183],"communication":[56,168],"costs,":[57],"needed":[59],"number":[60],"iterations,":[62],"latency":[64,186],"each":[66],"iteration":[67],"accuracy":[70,215],"trained":[73],"model":[74,214],"because":[75],"\u201cchurns\u201d":[78,218],"(i.e.,":[79,145],"devices":[80],"frequently":[81],"joining":[82],"leaving":[84],"network).":[86],"Existing":[87],"research":[88],"leverages":[89],"different":[90],"network":[91,108],"topologies":[92],"improve":[94],"learning.":[99,127],"this":[101],"paper,":[102],"we":[103],"propose":[104],"a":[105,137],"novel":[106],"hybrid":[107,178,199],"topology":[109],"design":[110,181,201],"that":[111,197],"integrates":[112],"ring":[113,139],"(R)":[114],"n-ary":[116,154],"tree":[117,156],"(T)":[118],"provide":[120],"flexible":[121],"adaptive":[123],"convergecast":[124,155,180],"Specifically,":[128],"multiple":[129],"participated":[130],"peers":[131],"within":[132],"one-hop":[133],"are":[134],"formed":[135,158],"as":[136,187,219],"adapt":[141],"device":[143],"dynamics":[144],"\u201cchurns\u201d)":[146],"carry":[148],"out":[149],"cooperation":[151],"shuffling;":[152],"an":[153],"from":[159],"rings":[161],"assure":[166],"efficiency.":[169],"Theoretical":[170],"analysis":[171],"shows":[172,196],"superiority":[174],"proposed":[177],"(R+T)":[179,200],"compared":[188,220],"existing":[190],"topologies.":[191],"Prototype-based":[192],"simulation":[193],"on":[194],"CloudLab":[195],"able":[203],"reduce":[205],"rounds":[207],"iterations":[209],"while":[210],"achieving":[211],"best":[213],"under":[216],"state":[223],"art.":[226]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}