{"id":"https://openalex.org/W7147239350","doi":"https://doi.org/10.1109/cnml68938.2026.11453225","title":"H-GINA: Accelerating Distributed Training via Hierarchical In-Network Aggregation with Multi-Objective Optimization","display_name":"H-GINA: Accelerating Distributed Training via Hierarchical In-Network Aggregation with Multi-Objective Optimization","publication_year":2026,"publication_date":"2026-01-30","ids":{"openalex":"https://openalex.org/W7147239350","doi":"https://doi.org/10.1109/cnml68938.2026.11453225"},"language":null,"primary_location":{"id":"doi:10.1109/cnml68938.2026.11453225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11453225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","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/A5132586642","display_name":"Yifei Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I4392021250","display_name":"State Key Laboratory of Networking and Switching Technology","ror":"https://ror.org/00qtv5q45","country_code":null,"type":"facility","lineage":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yifei Zhao","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024367327","display_name":"Fan Yang","orcid":"https://orcid.org/0000-0002-4213-2517"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I4392021250","display_name":"State Key Laboratory of Networking and Switching Technology","ror":"https://ror.org/00qtv5q45","country_code":null,"type":"facility","lineage":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Yang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5132586642"],"corresponding_institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4392021250"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.94314655,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"924","last_page":"931"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10714","display_name":"Software-Defined Networks and 5G","score":0.7597000002861023,"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"}},"topics":[{"id":"https://openalex.org/T10714","display_name":"Software-Defined Networks and 5G","score":0.7597000002861023,"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.1881999969482422,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.021400000900030136,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6953999996185303},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.6122999787330627},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5938000082969666},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5333999991416931},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.5328999757766724},{"id":"https://openalex.org/keywords/rounding","display_name":"Rounding","score":0.4909999966621399},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.41819998621940613},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.39010000228881836},{"id":"https://openalex.org/keywords/data-aggregator","display_name":"Data aggregator","score":0.37369999289512634}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7782999873161316},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6953999996185303},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.6122999787330627},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5938000082969666},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5855000019073486},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5333999991416931},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.5328999757766724},{"id":"https://openalex.org/C136625980","wikidata":"https://www.wikidata.org/wiki/Q663208","display_name":"Rounding","level":2,"score":0.4909999966621399},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.41819998621940613},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.39010000228881836},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.37369999289512634},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.3700999915599823},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.3433000147342682},{"id":"https://openalex.org/C195563490","wikidata":"https://www.wikidata.org/wiki/Q180368","display_name":"Network congestion","level":3,"score":0.3393999934196472},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.3368000090122223},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.32670000195503235},{"id":"https://openalex.org/C557945733","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Data transmission","level":2,"score":0.31369999051094055},{"id":"https://openalex.org/C138959212","wikidata":"https://www.wikidata.org/wiki/Q1806783","display_name":"Load balancing (electrical power)","level":3,"score":0.31150001287460327},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.31060001254081726},{"id":"https://openalex.org/C2779370713","wikidata":"https://www.wikidata.org/wiki/Q357554","display_name":"Load management","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.28450000286102295},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2736000120639801},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.2696000039577484},{"id":"https://openalex.org/C192126672","wikidata":"https://www.wikidata.org/wiki/Q1068715","display_name":"Telecommunications network","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C200157131","wikidata":"https://www.wikidata.org/wiki/Q4854763","display_name":"Bandwidth allocation","level":3,"score":0.2590999901294708},{"id":"https://openalex.org/C2780945871","wikidata":"https://www.wikidata.org/wiki/Q194274","display_name":"Backup","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cnml68938.2026.11453225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11453225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","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":23,"referenced_works":["https://openalex.org/W2060393849","https://openalex.org/W2194775991","https://openalex.org/W2975712713","https://openalex.org/W4242634435","https://openalex.org/W4285327707","https://openalex.org/W4321484191","https://openalex.org/W4327911839","https://openalex.org/W4385357021","https://openalex.org/W4385731932","https://openalex.org/W4386230822","https://openalex.org/W4386260612","https://openalex.org/W4386361554","https://openalex.org/W4386365337","https://openalex.org/W4386634514","https://openalex.org/W4387869602","https://openalex.org/W4389722097","https://openalex.org/W4389989295","https://openalex.org/W4394892714","https://openalex.org/W4396736180","https://openalex.org/W4399727769","https://openalex.org/W4399849412","https://openalex.org/W4402897297","https://openalex.org/W4407938690"],"related_works":[],"abstract_inverted_index":{"In-Network":[0],"Aggregation":[1],"(INA)":[2],"significantly":[3],"accelerates":[4],"distributed":[5],"training":[6],"by":[7,135,143,148],"offloading":[8],"computation":[9],"to":[10,32,72,110,137,150,163],"programmable":[11],"switches.":[12],"However,":[13],"existing":[14],"INA":[15],"strategies":[16],"often":[17],"overlook":[18],"the":[19,91,114,121],"inherent":[20],"trade-off":[21],"between":[22],"communication":[23,75,133],"overhead":[24,134],"and":[25,29,41,77,94,139,160],"aggregation":[26,66,78,99],"completion":[27],"time,":[28],"they":[30],"fail":[31],"efficiently":[33],"schedule":[34],"variable-sized":[35],"gradient":[36,53,65,108],"blocks":[37,109],"under":[38],"strict":[39],"bandwidth":[40],"memory":[42],"constraints.":[43],"To":[44],"address":[45],"these":[46],"challenges,":[47],"we":[48],"propose":[49],"H-GINA,":[50],"a":[51,68,82,86,102],"hybrid":[52],"scheduling":[54],"framework":[55],"tailored":[56],"for":[57,97],"hierarchical":[58],"data":[59],"center":[60],"networks":[61],"(DCNs).":[62],"We":[63],"formulate":[64],"as":[67],"multi-objective":[69],"optimization":[70],"problem":[71],"simultaneously":[73],"minimize":[74],"cost":[76],"time.":[79],"H-GINA":[80,128,153],"employs":[81],"two-stage":[83],"algorithm:":[84],"first,":[85],"linear":[87],"programming":[88],"relaxation":[89],"derives":[90],"optimal":[92],"probability":[93],"transmission":[95],"rate":[96],"different":[98,164],"modes;":[100],"second,":[101],"block-size-aware":[103],"deterministic":[104],"rounding":[105],"strategy":[106],"maps":[107],"specific":[111],"modes,":[112],"ensuring":[113],"actual":[115],"traffic":[116,147],"distribution":[117],"strictly":[118],"aligns":[119],"with":[120],"theoretical":[122],"optimum.":[123],"Experimental":[124],"results":[125],"demonstrate":[126],"that":[127],"outperforms":[129],"state-of-the-art":[130],"solutions,":[131],"reducing":[132],"up":[136,149],"66%":[138],"mitigating":[140],"incast":[141],"congestion":[142],"decreasing":[144],"PS":[145],"ingress":[146],"82%.":[151],"Furthermore,":[152],"exhibits":[154],"robust":[155],"scalability":[156],"in":[157],"dense":[158],"clusters":[159],"flexible":[161],"adaptability":[162],"performance":[165],"objectives.":[166]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}
