{"id":"https://openalex.org/W4300009903","doi":"https://doi.org/10.1109/icc45855.2022.9838659","title":"Towards Energy Efficient Resource Allocation: When Green Mobile Edge Computing Meets Multi-Agent Deep Reinforcement Learning","display_name":"Towards Energy Efficient Resource Allocation: When Green Mobile Edge Computing Meets Multi-Agent Deep Reinforcement Learning","publication_year":2022,"publication_date":"2022-05-16","ids":{"openalex":"https://openalex.org/W4300009903","doi":"https://doi.org/10.1109/icc45855.2022.9838659"},"language":"en","primary_location":{"id":"doi:10.1109/icc45855.2022.9838659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9838659","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2022 - 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/A5100740877","display_name":"Yang Xiao","orcid":"https://orcid.org/0000-0001-6897-5531"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Xiao","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Artificial Intelligence,Beijing,China","School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014110901","display_name":"Yuqian Song","orcid":"https://orcid.org/0000-0002-8495-3487"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuqian Song","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Artificial Intelligence,Beijing,China","School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100362109","display_name":"Jun Liu","orcid":"https://orcid.org/0000-0003-4007-6109"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Liu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,School of Artificial Intelligence,Beijing,China","School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7841,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.92793914,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4056","last_page":"4061"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9986000061035156,"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":0.9986000061035156,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.992900013923645,"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"}},{"id":"https://openalex.org/T11392","display_name":"Energy Harvesting in Wireless Networks","score":0.9894000291824341,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.876393735408783},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8217605352401733},{"id":"https://openalex.org/keywords/mobile-edge-computing","display_name":"Mobile edge computing","score":0.7183829545974731},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7180073261260986},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6690908074378967},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.6501226425170898},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.5715996026992798},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.5034288763999939},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.43854427337646484},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.41560977697372437},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.33381426334381104},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3082888722419739},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27044808864593506},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09950149059295654}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.876393735408783},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8217605352401733},{"id":"https://openalex.org/C2776061582","wikidata":"https://www.wikidata.org/wiki/Q25325231","display_name":"Mobile edge computing","level":3,"score":0.7183829545974731},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7180073261260986},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6690908074378967},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.6501226425170898},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.5715996026992798},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.5034288763999939},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.43854427337646484},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.41560977697372437},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.33381426334381104},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3082888722419739},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27044808864593506},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09950149059295654},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc45855.2022.9838659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9838659","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2022 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2003192648","https://openalex.org/W2088006206","https://openalex.org/W2145339207","https://openalex.org/W2594560857","https://openalex.org/W2624989916","https://openalex.org/W2736601468","https://openalex.org/W2746553466","https://openalex.org/W2788350651","https://openalex.org/W2898035736","https://openalex.org/W2969195240","https://openalex.org/W2998709521","https://openalex.org/W3174818244","https://openalex.org/W3187829000","https://openalex.org/W3207745675","https://openalex.org/W6741002519","https://openalex.org/W6802718327"],"related_works":["https://openalex.org/W4361251304","https://openalex.org/W3024547383","https://openalex.org/W4210813012","https://openalex.org/W3174690704","https://openalex.org/W2968424451","https://openalex.org/W4221092438","https://openalex.org/W4385335479","https://openalex.org/W2905685817","https://openalex.org/W2730940305","https://openalex.org/W4207020266"],"abstract_inverted_index":{"Mobile":[0],"edge":[1,10],"computing":[2,6],"(MEC)":[3],"extends":[4],"the":[5,9,25,31,35,50,74,88],"power":[7],"to":[8,22,86],"of":[11,27,37,90,107],"communication":[12,28],"networks,":[13],"which":[14],"has":[15,43],"been":[16,45],"considered":[17],"as":[18],"a":[19,62],"promising":[20],"technology":[21],"further":[23],"improve":[24],"quality":[26],"services":[29],"in":[30,105],"near":[32],"future.":[33],"Nevertheless,":[34],"issue":[36],"MEC-empowered":[38],"energy":[39,52],"efficient":[40],"resource":[41,69],"allocation":[42,70],"not":[44],"well":[46],"studied.":[47],"To":[48],"maximize":[49],"longterm":[51],"efficiency":[53],"for":[54],"green":[55],"MEC-enabled":[56],"heterogeneous":[57],"networks":[58],"(HetNets),":[59],"we":[60],"proposed":[61,81,98],"decentralized":[63],"multi-agent":[64],"deep":[65],"reinforcement":[66],"learning":[67],"(MADRL)":[68],"algorithm.":[71],"Based":[72],"on":[73],"proximal":[75],"policy":[76],"optimization":[77],"(PPO)":[78],"framework,":[79],"our":[80,97],"algorithm":[82,99],"enables":[83],"observation":[84],"exchange":[85],"coordinate":[87],"policies":[89],"multiple":[91],"agents.":[92],"Simulation":[93],"results":[94],"show":[95],"that":[96],"significantly":[100],"outperforms":[101],"three":[102],"baseline":[103],"methods":[104],"terms":[106],"effectiveness,":[108],"robustness,":[109],"and":[110],"scalability.":[111]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
