{"id":"https://openalex.org/W4399154755","doi":"https://doi.org/10.1109/wf-iot58464.2023.10539572","title":"Improving Mobile Edge Computing Orchestration Using Deep Reinforcement Learning Through Environment Predictions","display_name":"Improving Mobile Edge Computing Orchestration Using Deep Reinforcement Learning Through Environment Predictions","publication_year":2023,"publication_date":"2023-10-12","ids":{"openalex":"https://openalex.org/W4399154755","doi":"https://doi.org/10.1109/wf-iot58464.2023.10539572"},"language":"en","primary_location":{"id":"doi:10.1109/wf-iot58464.2023.10539572","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/wf-iot58464.2023.10539572","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 9th World Forum on Internet of Things (WF-IoT)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5052910846","display_name":"Eliana Neuza Silva","orcid":"https://orcid.org/0009-0008-7598-4805"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Eliana Neuza Silva","raw_affiliation_strings":["Instituto Superior Técnico, Universidade de Lisboa,Lisbon,Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto Superior Técnico, Universidade de Lisboa,Lisbon,Portugal","institution_ids":["https://openalex.org/I141596103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061404776","display_name":"Fernando M. Silva","orcid":"https://orcid.org/0000-0001-9959-3798"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Fernando Mira da Silva","raw_affiliation_strings":["Instituto Superior Técnico, Universidade de Lisboa,Lisbon,Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto Superior Técnico, Universidade de Lisboa,Lisbon,Portugal","institution_ids":["https://openalex.org/I141596103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I141596103"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9954000115394592,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/orchestration","display_name":"Orchestration","score":0.864639163017273},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8638061285018921},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8361485004425049},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.7153599262237549},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.4923657178878784},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.49134984612464905},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47553586959838867},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4710666537284851},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4500584304332733},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4443843960762024},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.42316144704818726},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4201948046684265},{"id":"https://openalex.org/keywords/quality-of-experience","display_name":"Quality of experience","score":0.41029125452041626},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3221932649612427},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.27721285820007324},{"id":"https://openalex.org/keywords/quality-of-service","display_name":"Quality of service","score":0.25620269775390625},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.13383308053016663}],"concepts":[{"id":"https://openalex.org/C199168358","wikidata":"https://www.wikidata.org/wiki/Q3367000","display_name":"Orchestration","level":3,"score":0.864639163017273},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8638061285018921},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8361485004425049},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.7153599262237549},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.4923657178878784},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.49134984612464905},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47553586959838867},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4710666537284851},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4500584304332733},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4443843960762024},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42316144704818726},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4201948046684265},{"id":"https://openalex.org/C2779333187","wikidata":"https://www.wikidata.org/wiki/Q3132648","display_name":"Quality of experience","level":3,"score":0.41029125452041626},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3221932649612427},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.27721285820007324},{"id":"https://openalex.org/C5119721","wikidata":"https://www.wikidata.org/wiki/Q220501","display_name":"Quality of service","level":2,"score":0.25620269775390625},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.13383308053016663},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wf-iot58464.2023.10539572","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/wf-iot58464.2023.10539572","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 9th World Forum on Internet of Things (WF-IoT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W596823783","https://openalex.org/W1949900164","https://openalex.org/W1987228002","https://openalex.org/W2012237473","https://openalex.org/W2906687478","https://openalex.org/W2917483248","https://openalex.org/W2969304542","https://openalex.org/W2980360843","https://openalex.org/W2982493294","https://openalex.org/W2988930013","https://openalex.org/W3004417498","https://openalex.org/W3010178570","https://openalex.org/W3089957928","https://openalex.org/W3110668685","https://openalex.org/W3158733437","https://openalex.org/W4200175666","https://openalex.org/W4200372040","https://openalex.org/W4206044098","https://openalex.org/W4293104538","https://openalex.org/W4307220356","https://openalex.org/W4384157909"],"related_works":["https://openalex.org/W79913212","https://openalex.org/W2094884983","https://openalex.org/W2378898096","https://openalex.org/W560952460","https://openalex.org/W2290927522","https://openalex.org/W4310007397","https://openalex.org/W4213154119","https://openalex.org/W2770104838","https://openalex.org/W2896418752","https://openalex.org/W4383749321"],"abstract_inverted_index":{"Edge":[0],"Computing":[1],"(EC)":[2],"in":[3,52,113,141,151],"Hospital":[4,117],"and":[5,22,42,102,122,150],"Healthcare":[6],"environments":[7],"require":[8],"an":[9],"efficient":[10],"offloading":[11,56,159],"orchestration":[12,57,139],"between":[13],"Internet":[14],"of":[15,28,99,107,130,143,153],"Things":[16],"(IoT)":[17],"sensors,":[18],"mobile":[19,123],"smart":[20],"devices,":[21],"the":[23,104,128,137,147,162],"network":[24],"edge,":[25],"since":[26],"many":[27],"their":[29],"applications":[30],"(APP)":[31],"have":[32,67],"low":[33],"latency":[34],"constraints":[35],"that":[36,65,127],"are":[37,72],"linked":[38],"to":[39,86,157],"critical":[40],"health":[41],"safety":[43],"demands.":[44],"This":[45],"work":[46],"focuses":[47],"on":[48,60],"using":[49],"environment":[50,118],"predictions":[51,71],"a":[53,54,114],"novel":[55],"algorithm":[58],"based":[59],"Deep":[61,82],"Reinforcement":[62],"Learning":[63],"(DRL)":[64],"we":[66],"introduced":[68],"before.":[69],"The":[70],"obtained":[73],"by":[74],"combining":[75],"Long":[76],"Short":[77],"Memory":[78],"(LSTM)":[79],"with":[80,119,132],"three":[81],"Neural":[83],"Networks":[84],"(DNN),":[85],"assess":[87],"APP's":[88],"tasks":[89],"dependency,":[90],"predict":[91,103],"possible":[92],"next":[93],"tasks,":[94],"estimate":[95],"future":[96],"CPU":[97],"availability":[98],"edge":[100],"nodes":[101],"mobility":[105],"path":[106],"devices.":[108,124],"We":[109],"test":[110],"our":[111],"solution":[112],"dynamic":[115],"EC":[116],"different":[120],"IoT":[121],"Tests":[125],"show":[126],"addition":[129],"LSTM":[131],"several":[133],"DNNs":[134],"significantly":[135],"improves":[136],"DRL":[138],"algorithm,":[140],"terms":[142],"task":[144],"completion":[145],"within":[146],"delay":[148],"requirements":[149],"Quality":[152],"Experience":[154],"(QoE),":[155],"compared":[156],"other":[158],"solutions":[160],"from":[161],"literature.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}