{"id":"https://openalex.org/W4414539431","doi":"https://doi.org/10.1109/icc52391.2025.11161754","title":"Green Reinforcement and Split Learning Framework for Edge-Fog-Cloud Continuum in 6G Networks","display_name":"Green Reinforcement and Split Learning Framework for Edge-Fog-Cloud Continuum in 6G Networks","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414539431","doi":"https://doi.org/10.1109/icc52391.2025.11161754"},"language":"en","primary_location":{"id":"doi:10.1109/icc52391.2025.11161754","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.1109/ICC52391.2025.11161754","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Amit Dua","orcid":null},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Amit Dua","raw_affiliation_strings":["Durham University,Department of Computer Science,Durham,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Durham University,Department of Computer Science,Durham,United Kingdom","institution_ids":["https://openalex.org/I190082696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063414144","display_name":"Anish Jindal","orcid":"https://orcid.org/0000-0002-3052-2892"},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Anish Jindal","raw_affiliation_strings":["Durham University,Department of Computer Science,Durham,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Durham University,Department of Computer Science,Durham,United Kingdom","institution_ids":["https://openalex.org/I190082696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036704324","display_name":"Gagangeet Singh Aujla","orcid":"https://orcid.org/0000-0002-2870-8938"},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gagangeet Singh Aujla","raw_affiliation_strings":["Durham University,Department of Computer Science,Durham,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Durham University,Department of Computer Science,Durham,United Kingdom","institution_ids":["https://openalex.org/I190082696"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100694341","display_name":"Hongjian Sun","orcid":"https://orcid.org/0000-0001-8660-8081"},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hongjian Sun","raw_affiliation_strings":["Durham University,Department of Engineering,Durham,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Durham University,Department of Engineering,Durham,United Kingdom","institution_ids":["https://openalex.org/I190082696"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I190082696"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3479","last_page":"3484"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9580000042915344,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9580000042915344,"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/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9211000204086304,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8026999831199646},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6913999915122986},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6025000214576721},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5508999824523926},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.4733000099658966},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45210000872612},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4490000009536743},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.38749998807907104}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8026999831199646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7366999983787537},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6913999915122986},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6025000214576721},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5828999876976013},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5508999824523926},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.4733000099658966},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45210000872612},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4490000009536743},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.38749998807907104},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37869998812675476},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3522000014781952},{"id":"https://openalex.org/C190793597","wikidata":"https://www.wikidata.org/wiki/Q189768","display_name":"Application layer","level":3,"score":0.3215999901294708},{"id":"https://openalex.org/C158156997","wikidata":"https://www.wikidata.org/wiki/Q1416645","display_name":"Models of communication","level":2,"score":0.3043999969959259},{"id":"https://openalex.org/C46637626","wikidata":"https://www.wikidata.org/wiki/Q6693015","display_name":"Low latency (capital markets)","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.29420000314712524},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C192126672","wikidata":"https://www.wikidata.org/wiki/Q1068715","display_name":"Telecommunications network","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.2743000090122223},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2630000114440918}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icc52391.2025.11161754","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","raw_type":"proceedings-article"},{"id":"pmh:oai:durham-repository.worktribe.com:3342063","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ICC52391.2025.11161754","pdf_url":null,"source":{"id":"https://openalex.org/S4306400188","display_name":"Durham Research Online (Durham University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I190082696","host_organization_name":"Durham University","host_organization_lineage":["https://openalex.org/I190082696"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Presentation / Conference Contribution"}],"best_oa_location":{"id":"pmh:oai:durham-repository.worktribe.com:3342063","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ICC52391.2025.11161754","pdf_url":null,"source":{"id":"https://openalex.org/S4306400188","display_name":"Durham Research Online (Durham University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I190082696","host_organization_name":"Durham University","host_organization_lineage":["https://openalex.org/I190082696"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Presentation / Conference Contribution"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3053266086","display_name":null,"funder_award_id":"EP/X040518/1,EP/Y037421/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2002182716","https://openalex.org/W2295124130","https://openalex.org/W2783130023","https://openalex.org/W2947714655","https://openalex.org/W2969195240","https://openalex.org/W3215554746","https://openalex.org/W4205504318","https://openalex.org/W4387397235","https://openalex.org/W4390771634","https://openalex.org/W4398249507"],"related_works":[],"abstract_inverted_index":{"6G":[0,49],"applications":[1],"rely":[2],"on":[3],"data-intensive":[4],"AI":[5],"models":[6,184],"for":[7,103,115,123,134,162],"network":[8],"optimization.":[9],"These":[10],"demand":[11],"a":[12,65],"scalable":[13],"and":[14,36,98,125,164,172,188],"energyefficient":[15],"framework":[16,67],"to":[17,30,41,55,93,100,112],"handle":[18],"massive":[19],"device":[20,131,141],"networks":[21],"with":[22],"stringent":[23],"latency":[24,171],"requirements":[25],"which":[26],"current":[27],"solutions":[28,44,47],"struggle":[29],"support.":[31],"Although":[32],"reinforcement":[33],"learning":[34,38,122,128],"(RL)":[35],"split":[37,121],"have":[39,50],"matured":[40],"provide":[42],"commercial":[43],"elsewhere.":[45],"Current":[46],"in":[48,166,183],"not":[51],"used":[52],"them":[53],"systematically":[54],"achieve":[56],"the":[57,73,90,96,127,143,179],"sustainability":[58],"goals.":[59],"In":[60],"this":[61],"paper,":[62],"we":[63],"propose":[64],"three-layer":[66],"that":[68],"minimizes":[69],"energy":[70,169],"consumption":[71],"of":[72,77,81,168,181],"communication":[74,124],"system":[75,97,148],"capable":[76],"handling":[78],"large":[79],"number":[80],"devices.":[82],"The":[83,105,154,175],"proposed":[84,155],"solution":[85],"uses":[86],"RL":[87,145],"agents":[88],"at":[89,129],"edge":[91,140],"layer":[92,102,114],"mathematically":[94],"model":[95,117,136,146],"communicate":[99],"fog":[101,187],"aggregation.":[104],"aggregated":[106],"feature":[107],"maps":[108],"are":[109,132],"further":[110],"communicated":[111,133],"cloud":[113,189],"global":[116,135],"training.":[118],"We":[119],"use":[120],"training,":[126],"each":[130],"creation":[137],"effectively.":[138],"Each":[139],"improves":[142],"overall":[144],"where":[147],"matures":[149],"quickly":[150],"consuming":[151],"minimal":[152],"energy.":[153],"framework's":[156],"efficacy":[157],"has":[158],"been":[159],"tested":[160],"extensively":[161],"accuracy":[163],"scalability,":[165],"terms":[167],"consumption,":[170],"memory":[173],"utilizations.":[174],"simulation":[176],"results":[177],"validate":[178],"claims":[180],"maturity":[182],"across":[185],"edge,":[186],"levels.":[190]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}