{"id":"https://openalex.org/W4401567907","doi":"https://doi.org/10.1109/cloud-summit61220.2024.00023","title":"Optimizing Edge-Cloud Server Selection: A Multi-Objective Deep Reinforcement Learning Approach","display_name":"Optimizing Edge-Cloud Server Selection: A Multi-Objective Deep Reinforcement Learning Approach","publication_year":2024,"publication_date":"2024-06-27","ids":{"openalex":"https://openalex.org/W4401567907","doi":"https://doi.org/10.1109/cloud-summit61220.2024.00023"},"language":"en","primary_location":{"id":"doi:10.1109/cloud-summit61220.2024.00023","doi":"https://doi.org/10.1109/cloud-summit61220.2024.00023","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cloud-summit61220.2024.00023","pdf_url":null,"source":{"id":"https://openalex.org/S7407087509","display_name":"IEEE Cloud Summit","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2024 IEEE Cloud Summit","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5113333644","display_name":"Huyen-Trang Le","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Huyen-Trang Le","raw_affiliation_strings":["School of Information and Communications Technology, Hanoi University of Science and Technology (HUST),Hanoi,Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communications Technology, Hanoi University of Science and Technology (HUST),Hanoi,Vietnam","institution_ids":["https://openalex.org/I94518387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053163348","display_name":"Hai Anh Tran","orcid":"https://orcid.org/0000-0002-6215-4879","observed_orcids":["https://orcid.org/0000-0002-6215-4879"]},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Hai-Anh Tran","raw_affiliation_strings":["School of Information and Communications Technology, Hanoi University of Science and Technology (HUST),Hanoi,Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communications Technology, Hanoi University of Science and Technology (HUST),Hanoi,Vietnam","institution_ids":["https://openalex.org/I94518387"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021490756","display_name":"Truong X. Tran","orcid":"https://orcid.org/0000-0002-3214-010X","observed_orcids":["https://orcid.org/0000-0002-3214-010X"]},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Truong X. Tran","raw_affiliation_strings":["School of Science, Engineering and Technology Penn State Harrisburg, The Pennsylvania State University,Middletown,PA,United States,17057"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Science, Engineering and Technology Penn State Harrisburg, The Pennsylvania State University,Middletown,PA,United States,17057","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6236,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.54859466,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"101","last_page":"106"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9775000214576721,"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":0.9775000214576721,"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":0.016100000590085983,"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/T14098","display_name":"Energy Efficiency in Computing","score":0.0017000000225380063,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/multi-objective-deep-reinforcement-learning","display_name":"multi-objective deep reinforcement learning","score":0.8960000276565552},{"id":"https://openalex.org/keywords/proximal-policy-optimization","display_name":"proximal policy optimization","score":0.9150000214576721},{"id":"https://openalex.org/keywords/resource-scheduling","display_name":"resource scheduling","score":0.972000002861023},{"id":"https://openalex.org/keywords/state-encoding","display_name":"state encoding","score":0.8640000224113464},{"id":"https://openalex.org/keywords/reward-function-design","display_name":"reward function design","score":0.9789999723434448},{"id":"https://openalex.org/keywords/edge-computing","display_name":"edge computing","score":0.5920000076293945},{"id":"https://openalex.org/keywords/network-latency","display_name":"network latency","score":0.6660000085830688},{"id":"https://openalex.org/keywords/link-utilization","display_name":"link utilization","score":0.8059999942779541}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7855056524276733},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7706413269042969},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6964997053146362},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6783337593078613},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6442137360572815},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4352361261844635},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4057885706424713},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39849650859832764},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3528043031692505},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.23615241050720215}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cloud-summit61220.2024.00023","doi":"https://doi.org/10.1109/cloud-summit61220.2024.00023","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cloud-summit61220.2024.00023","pdf_url":null,"source":{"id":"https://openalex.org/S7407087509","display_name":"IEEE Cloud Summit","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2024 IEEE Cloud Summit","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.7207000255584717}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1191599655","https://openalex.org/W1483039810","https://openalex.org/W2102660061","https://openalex.org/W2142300547","https://openalex.org/W2736601468","https://openalex.org/W2903836693","https://openalex.org/W2933541663","https://openalex.org/W2979224496","https://openalex.org/W2985229174","https://openalex.org/W2998567988","https://openalex.org/W3112717400","https://openalex.org/W3154679551","https://openalex.org/W3156442476","https://openalex.org/W3159352788","https://openalex.org/W3184322752","https://openalex.org/W3197876962","https://openalex.org/W3209477841","https://openalex.org/W4206383810","https://openalex.org/W4226342902","https://openalex.org/W4280560452","https://openalex.org/W4390098664"],"related_works":["https://openalex.org/W4404238474","https://openalex.org/W3209283715","https://openalex.org/W4388240184","https://openalex.org/W4400732033","https://openalex.org/W4387912742","https://openalex.org/W4385261078","https://openalex.org/W4382681709","https://openalex.org/W4213067231","https://openalex.org/W4390589764","https://openalex.org/W7161542846"],"abstract_inverted_index":{"Edge":[0],"computing":[1],"presents":[2],"an":[3],"efficient":[4],"solution":[5],"for":[6],"alleviating":[7],"the":[8,27,42,88,96,99],"workload":[9],"on":[10],"cloud":[11,18,51],"servers.":[12],"However,":[13],"effectively":[14],"selecting":[15],"edge":[16,48],"and":[17,36,50,81],"servers":[19],"poses":[20],"a":[21,55,75,82],"significant":[22],"challenge.":[23],"Numerous":[24],"factors":[25],"influence":[26],"performance":[28],"of":[29,44,90,98],"this":[30],"server":[31,45,52,108],"selection":[32,46,109],"problem,":[33],"including":[34],"delays":[35],"link":[37],"utilization.":[38],"This":[39],"paper":[40],"addresses":[41],"issue":[43],"in":[47],"networks":[49],"clusters.":[53],"Specifically,":[54],"Multi-Objective":[56],"Deep":[57],"Reinforcement":[58],"Learning":[59],"(MORL)-based":[60],"resource":[61],"scheduling":[62],"scheme":[63],"that":[64],"integrates":[65],"Proximal":[66],"Policy":[67],"Optimization":[68],"(PPO)":[69],"is":[70],"proposed.":[71],"Furthermore,":[72],"we":[73],"introduce":[74],"meticulously":[76],"designed":[77],"state":[78],"encoding":[79],"method":[80],"sophisticated":[83],"reward":[84],"function":[85],"to":[86,106],"enhance":[87],"accuracy":[89],"utility":[91],"computations.":[92],"Experimental":[93],"findings":[94],"underscore":[95],"efficacy":[97],"MORL":[100],"scheme,":[101],"demonstrating":[102],"substantial":[103],"improvement":[104],"compared":[105],"existing":[107],"algorithms.":[110]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-10-05T09:50:58.205359","created_date":"2024-08-15T00:00:00"}