{"id":"https://openalex.org/W3166824036","doi":"https://doi.org/10.1109/tvt.2021.3089431","title":"FedSVRG Based Communication Efficient Scheme for Federated Learning in MEC Networks","display_name":"FedSVRG Based Communication Efficient Scheme for Federated Learning in MEC Networks","publication_year":2021,"publication_date":"2021-06-15","ids":{"openalex":"https://openalex.org/W3166824036","doi":"https://doi.org/10.1109/tvt.2021.3089431","mag":"3166824036"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2021.3089431","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2021.3089431","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","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/A5100322085","display_name":"Dawei Chen","orcid":"https://orcid.org/0000-0002-4162-1423"},"institutions":[{"id":"https://openalex.org/I44461941","display_name":"University of Houston","ror":"https://ror.org/048sx0r50","country_code":"US","type":"education","lineage":["https://openalex.org/I44461941"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dawei Chen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA"],"raw_orcid":"https://orcid.org/0000-0002-4162-1423","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA","institution_ids":["https://openalex.org/I44461941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034052371","display_name":"Choong Seon Hong","orcid":"https://orcid.org/0000-0003-3484-7333"},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Choong Seon Hong","raw_affiliation_strings":["Department of Computer Science and Engineering, Kyung Hee University, Yongin-si, Gyeonggi-do, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-3484-7333","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Kyung Hee University, Yongin-si, Gyeonggi-do, South Korea","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112435305","display_name":"Yiyong Zha","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiyong Zha","raw_affiliation_strings":["Tencent Technology Co. Ltd., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Technology Co. Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100613465","display_name":"Yunfei Zhang","orcid":"https://orcid.org/0000-0001-8160-7995"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunfei Zhang","raw_affiliation_strings":["Tencent Technology Co. Ltd., Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-8160-7995","affiliations":[{"raw_affiliation_string":"Tencent Technology Co. Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100352274","display_name":"Xin Liu","orcid":"https://orcid.org/0000-0002-8272-9553"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Liu","raw_affiliation_strings":["Tencent Technology Co. Ltd., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Technology Co. Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063667378","display_name":"Zhu Han","orcid":"https://orcid.org/0000-0002-6606-5822"},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]},{"id":"https://openalex.org/I44461941","display_name":"University of Houston","ror":"https://ror.org/048sx0r50","country_code":"US","type":"education","lineage":["https://openalex.org/I44461941"]}],"countries":["KR","US"],"is_corresponding":false,"raw_author_name":"Zhu Han","raw_affiliation_strings":["Department of Computer Science and Engineering, Kyung Hee University, Seoul, South Korea","Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA"],"raw_orcid":"https://orcid.org/0000-0002-6606-5822","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Kyung Hee University, Seoul, South Korea","institution_ids":["https://openalex.org/I35928602"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA","institution_ids":["https://openalex.org/I44461941"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3202,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.90054773,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"70","issue":"7","first_page":"7300","last_page":"7304"},"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9966999888420105,"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":0.9574999809265137,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7746103405952454},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.6623485088348389},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.6262402534484863},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.625454843044281},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5844034552574158},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5413541197776794},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.5407403111457825},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4906703233718872},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.47465378046035767},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46738946437835693},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.46570947766304016},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43566399812698364},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.41734498739242554},{"id":"https://openalex.org/keywords/low-latency","display_name":"Low latency (capital markets)","score":0.41314437985420227},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3852057158946991},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2817084789276123},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18982729315757751},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.12180137634277344},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10013949871063232}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7746103405952454},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.6623485088348389},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.6262402534484863},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.625454843044281},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5844034552574158},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5413541197776794},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.5407403111457825},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4906703233718872},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.47465378046035767},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46738946437835693},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.46570947766304016},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43566399812698364},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.41734498739242554},{"id":"https://openalex.org/C46637626","wikidata":"https://www.wikidata.org/wiki/Q6693015","display_name":"Low latency (capital markets)","level":2,"score":0.41314437985420227},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3852057158946991},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2817084789276123},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18982729315757751},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.12180137634277344},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10013949871063232},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","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},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2021.3089431","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2021.3089431","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5699999928474426}],"awards":[{"id":"https://openalex.org/G2273964084","display_name":null,"funder_award_id":"CNS1717454","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"},{"id":"https://openalex.org/G3325918464","display_name":null,"funder_award_id":"CNS-1731424","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"},{"id":"https://openalex.org/G3554202431","display_name":null,"funder_award_id":"EARS-1839818","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"},{"id":"https://openalex.org/G7758496514","display_name":null,"funder_award_id":"CNS-1702850","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"}],"funders":[{"id":"https://openalex.org/F4320335353","display_name":"National Science Foundation of Sri Lanka","ror":"https://ror.org/010xaa060"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2107438106","https://openalex.org/W2530417694","https://openalex.org/W2535838896","https://openalex.org/W2947064482","https://openalex.org/W2963156201","https://openalex.org/W2963318081","https://openalex.org/W2989120265","https://openalex.org/W2989289980","https://openalex.org/W2999074226","https://openalex.org/W3010594930","https://openalex.org/W3014531610","https://openalex.org/W3095611529","https://openalex.org/W3105099026","https://openalex.org/W3111009493","https://openalex.org/W3124156460","https://openalex.org/W4297687186","https://openalex.org/W6676105031","https://openalex.org/W6790072066"],"related_works":["https://openalex.org/W2895097035","https://openalex.org/W4206903459","https://openalex.org/W2754816816","https://openalex.org/W4366280654","https://openalex.org/W3160167280","https://openalex.org/W3020853991","https://openalex.org/W4362706668","https://openalex.org/W4231621013","https://openalex.org/W3171021120","https://openalex.org/W3008318776"],"abstract_inverted_index":{"Recently,":[0],"a":[1,25,54,71,82,96,103],"novel":[2],"machine":[3,28],"learning":[4,20,29],"technique,":[5],"federated":[6,19,104,178],"learning,":[7],"attracts":[8],"ever-increasing":[9],"interests":[10],"from":[11,122],"academia":[12],"to":[13,22,70,75,85,111],"industry.":[14],"The":[15,157],"main":[16],"idea":[17],"of":[18,38,44,57,115],"is":[21,80,139],"collaboratively":[23],"train":[24],"global":[26],"optimal":[27],"model":[30,91],"among":[31],"all":[32],"the":[33,36,41,45,62,68,87,92,113,118,123,128,131,135,148,153,167],"participants.":[34,60],"During":[35],"process":[37],"parameter":[39],"updating,":[40],"communication":[42,168],"cost":[43,169],"system":[46,124],"or":[47],"network":[48],"can":[49,66,165],"be":[50],"extremely":[51],"huge":[52],"with":[53,172],"large":[55],"number":[56,114],"iterations":[58,116],"and":[59,120,126,152],"Although":[61],"edge":[63],"computing":[64],"paradigm":[65],"decrease":[67,112],"latency":[69],"certain":[72],"extent,":[73],"how":[74],"obtain":[76],"further":[77],"delay":[78],"reduction":[79],"still":[81],"challenge.":[83],"Therefore,":[84],"address":[86],"problem,":[88],"we":[89,101,142],"firstly":[90],"corresponding":[93,136],"problem":[94,151],"into":[95],"finite-sum":[97],"optimization":[98],"problem.":[99,156],"Then,":[100],"propose":[102],"stochastic":[105,174],"variance":[106],"reduced":[107],"gradient":[108,175],"based":[109,177],"method":[110,146,164],"between":[117],"participants":[119],"server":[121],"perspective,":[125],"guarantee":[127],"accuracy":[129],"at":[130],"same":[132],"time.":[133],"Meanwhile,":[134],"convergence":[137],"analysis":[138],"provided.":[140],"Finally,":[141],"test":[143],"our":[144,162],"proposed":[145,163],"on":[147],"linear":[149],"regression":[150,155],"logistic":[154],"simulation":[158],"results":[159],"show":[160],"that":[161],"reduce":[166],"significantly":[170],"compared":[171],"general":[173],"descent":[176],"learning.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}