{"id":"https://openalex.org/W4398787768","doi":"https://doi.org/10.1109/access.2024.3405411","title":"Multi-Objective Deep Reinforcement Learning for Efficient Workload Orchestration in Extreme Edge Computing","display_name":"Multi-Objective Deep Reinforcement Learning for Efficient Workload Orchestration in Extreme Edge Computing","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4398787768","doi":"https://doi.org/10.1109/access.2024.3405411"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3405411","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3405411","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10538273.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10538273.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071289369","display_name":"Zahra Safavifar","orcid":"https://orcid.org/0000-0001-8531-5068"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Zahra Safavifar","raw_affiliation_strings":["School of Computer Science, University College Dublin, Dublin 4, Ireland"],"raw_orcid":"https://orcid.org/0000-0001-8531-5068","affiliations":[{"raw_affiliation_string":"School of Computer Science, University College Dublin, Dublin 4, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040897068","display_name":"Eric Gyamfi","orcid":"https://orcid.org/0000-0002-0744-4208"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Eric Gyamfi","raw_affiliation_strings":["School of Computer Science, University College Dublin, Dublin 4, Ireland"],"raw_orcid":"https://orcid.org/0000-0002-0744-4208","affiliations":[{"raw_affiliation_string":"School of Computer Science, University College Dublin, Dublin 4, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029438479","display_name":"Eleni Mangina","orcid":"https://orcid.org/0000-0003-3374-0307"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Eleni Mangina","raw_affiliation_strings":["School of Computer Science, University College Dublin, Dublin 4, Ireland"],"raw_orcid":"https://orcid.org/0000-0003-3374-0307","affiliations":[{"raw_affiliation_string":"School of Computer Science, University College Dublin, Dublin 4, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088174565","display_name":"Fatemeh Golpayegani","orcid":"https://orcid.org/0000-0002-3712-6550"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Fatemeh Golpayegani","raw_affiliation_strings":["School of Computer Science, University College Dublin, Dublin 4, Ireland"],"raw_orcid":"https://orcid.org/0000-0002-3712-6550","affiliations":[{"raw_affiliation_string":"School of Computer Science, University College Dublin, Dublin 4, Ireland","institution_ids":["https://openalex.org/I100930933"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I100930933"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.7045,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.8467093,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"12","issue":null,"first_page":"74558","last_page":"74571"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9915000200271606,"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/T13553","display_name":"Age of Information Optimization","score":0.9742000102996826,"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/server","display_name":"Server","score":0.851665735244751},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8321574330329895},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.7112499475479126},{"id":"https://openalex.org/keywords/orchestration","display_name":"Orchestration","score":0.692912757396698},{"id":"https://openalex.org/keywords/mobile-edge-computing","display_name":"Mobile edge computing","score":0.6607422828674316},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5977259874343872},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5540353059768677},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.4859239161014557},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.443551242351532},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.365099161863327},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.32975268363952637},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.1937975287437439},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1638171672821045},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10048818588256836}],"concepts":[{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.851665735244751},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8321574330329895},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.7112499475479126},{"id":"https://openalex.org/C199168358","wikidata":"https://www.wikidata.org/wiki/Q3367000","display_name":"Orchestration","level":3,"score":0.692912757396698},{"id":"https://openalex.org/C2776061582","wikidata":"https://www.wikidata.org/wiki/Q25325231","display_name":"Mobile edge computing","level":3,"score":0.6607422828674316},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5977259874343872},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5540353059768677},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.4859239161014557},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.443551242351532},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.365099161863327},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.32975268363952637},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.1937975287437439},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1638171672821045},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10048818588256836},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"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/C558565934","wikidata":"https://www.wikidata.org/wiki/Q2743","display_name":"Musical","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3405411","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3405411","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10538273.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5c4e23e499f34f3b9fc2e54707ab6f97","is_oa":true,"landing_page_url":"https://doaj.org/article/5c4e23e499f34f3b9fc2e54707ab6f97","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 74558-74571 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3405411","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3405411","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10538273.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7316039843","display_name":"SFI Centre for Research Training in Machine Learning","funder_award_id":"18/CRT/6183","funder_id":"https://openalex.org/F4320320847","funder_display_name":"Science Foundation Ireland"}],"funders":[{"id":"https://openalex.org/F4320320847","display_name":"Science Foundation Ireland","ror":"https://ror.org/0271asj38"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4398787768.pdf"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W2145339207","https://openalex.org/W2252713824","https://openalex.org/W2335223849","https://openalex.org/W2516703745","https://openalex.org/W2558349963","https://openalex.org/W2615926310","https://openalex.org/W2733253862","https://openalex.org/W2736823879","https://openalex.org/W2768646057","https://openalex.org/W2782105028","https://openalex.org/W2799283631","https://openalex.org/W2807249129","https://openalex.org/W2808381205","https://openalex.org/W2887479174","https://openalex.org/W2890344874","https://openalex.org/W2897798676","https://openalex.org/W2911142008","https://openalex.org/W2920054549","https://openalex.org/W2942616607","https://openalex.org/W2959276766","https://openalex.org/W2970982242","https://openalex.org/W2979596121","https://openalex.org/W2980360843","https://openalex.org/W2987126276","https://openalex.org/W3010723141","https://openalex.org/W3013613527","https://openalex.org/W3016258889","https://openalex.org/W3042206064","https://openalex.org/W3047538493","https://openalex.org/W3089957928","https://openalex.org/W3103487703","https://openalex.org/W3104607803","https://openalex.org/W3110480290","https://openalex.org/W3118727533","https://openalex.org/W3123257271","https://openalex.org/W3204491243","https://openalex.org/W4200175666","https://openalex.org/W4214717370","https://openalex.org/W4214813921","https://openalex.org/W4233840023","https://openalex.org/W4293867902","https://openalex.org/W4320011080","https://openalex.org/W4366492854","https://openalex.org/W4386265299","https://openalex.org/W4391559419","https://openalex.org/W4392940561","https://openalex.org/W4394616323","https://openalex.org/W6757722641"],"related_works":["https://openalex.org/W4310007397","https://openalex.org/W4213154119","https://openalex.org/W2770104838","https://openalex.org/W2896418752","https://openalex.org/W4383749321","https://openalex.org/W3154796165","https://openalex.org/W4361251304","https://openalex.org/W3139051647","https://openalex.org/W2902693277","https://openalex.org/W4378977105"],"abstract_inverted_index":{"Workload":[0],"orchestration":[1],"at":[2],"the":[3,6,13,33,44,52,79,85,92,122,174],"edge":[4,88,126,158],"of":[5,16,35,124],"network":[7],"has":[8,28],"become":[9],"increasingly":[10],"challenging":[11],"with":[12,71,160],"ever-increasing":[14],"penetration":[15],"resource":[17,130,182],"demanding":[18],"mobile,":[19],"and":[20,42,61,83,128,135,156,189],"heterogeneous":[21],"devices":[22,127,159],"offering":[23],"low":[24],"latency":[25],"services.":[26],"Literature":[27],"addressed":[29],"this":[30,103],"challenge":[31],"assuming":[32],"availability":[34],"multi-access":[36],"Mobile":[37],"Edge":[38,147],"Computing":[39,148],"(MEC)":[40],"servers":[41,94,153],"placing":[43],"computing":[45,63,138],"tasks":[46],"related":[47],"to":[48,56,77,90,120,165],"such":[49],"services":[50],"on":[51],"MEC":[53,80,152],"servers.":[54],"However,":[55],"develop":[57],"a":[58,108],"more":[59,133],"sustainable":[60,134],"energy-efficient":[62],"paradigm,":[64],"for":[65,96,113,132],"applications":[66],"operating":[67],"in":[68,144,181,195],"stochastic":[69],"environments":[70],"unpredictable":[72,99],"workloads,":[73],"it":[74],"is":[75,119,142,154],"essential":[76],"minimize":[78,129],"servers\u2019":[81],"usage,":[82],"utilize":[84],"available":[86,155],"resource-constrained":[87,125],"devices,":[89],"keep":[91],"resourceful":[93],"idle":[95],"handling":[97],"any":[98],"larger":[100],"workload.":[101],"In":[102],"paper,":[104],"we":[105],"proposed":[106],"DEWOrch,":[107],"deep":[109],"reinforcement":[110],"Learning":[111],"algorithm":[112],"efficient":[114,137],"workload":[115],"orchestration.":[116],"DEWOrch\u2019s":[117],"aim":[118],"increase":[121],"utilization":[123],"waste":[131,183],"energy":[136,191],"solution.":[139],"This":[140],"model":[141],"evaluated":[143],"an":[145],"Extreme":[146],"environment,":[149],"where":[150],"no":[151],"only":[157],"constrained":[161],"capacity":[162],"are":[163],"used":[164],"perform":[166],"tasks.":[167],"The":[168],"results":[169],"show":[170],"that":[171],"DEWOrch":[172],"outperforms":[173],"state-of-the-art":[175],"methods":[176],"by":[177],"around":[178],"50%":[179],"decrease":[180],"while":[184],"improved":[185],"task":[186,194],"success":[187],"rate,":[188],"decreased":[190],"consumption":[192],"per":[193],"most":[196],"scenarios.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}