{"id":"https://openalex.org/W3210409505","doi":"https://doi.org/10.1109/tmc.2021.3123135","title":"Dynamic Reservation of Edge Servers via Deep Reinforcement Learning for Connected Vehicles","display_name":"Dynamic Reservation of Edge Servers via Deep Reinforcement Learning for Connected Vehicles","publication_year":2021,"publication_date":"2021-10-27","ids":{"openalex":"https://openalex.org/W3210409505","doi":"https://doi.org/10.1109/tmc.2021.3123135","mag":"3210409505"},"language":"en","primary_location":{"id":"doi:10.1109/tmc.2021.3123135","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2021.3123135","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Mobile Computing","raw_type":"journal-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/A5100462845","display_name":"Jiawei Zhang","orcid":"https://orcid.org/0000-0002-8634-1687"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiawei Zhang","raw_affiliation_strings":["UM-SJTU Joint Institute, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"UM-SJTU Joint Institute, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101436800","display_name":"Suhong Chen","orcid":"https://orcid.org/0000-0001-9482-2715"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Suhong Chen","raw_affiliation_strings":["UM-SJTU Joint Institute, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"UM-SJTU Joint Institute, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100348138","display_name":"Xudong Wang","orcid":"https://orcid.org/0000-0002-1353-1420"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xudong Wang","raw_affiliation_strings":["UM-SJTU Joint Institute, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"UM-SJTU Joint Institute, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000882682","display_name":"Yifei Zhu","orcid":"https://orcid.org/0000-0003-4352-6507"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifei Zhu","raw_affiliation_strings":["UM-SJTU Joint Institute, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"UM-SJTU Joint Institute, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100462845"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":1.2193,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.79187518,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"22","issue":"5","first_page":"2661","last_page":"2674"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9976999759674072,"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"}},"topics":[{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9976999759674072,"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/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9957000017166138,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.8550304770469666},{"id":"https://openalex.org/keywords/reservation","display_name":"Reservation","score":0.8206242322921753},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8157943487167358},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.8082727193832397},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6972635984420776},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5191192030906677},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.5169800519943237},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.5065475702285767},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4959186017513275},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.48638394474983215},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4683857262134552},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.464380145072937},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41071105003356934},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.38626617193222046},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.33443108201026917},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3286401033401489},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.07773396372795105}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8550304770469666},{"id":"https://openalex.org/C2777632111","wikidata":"https://www.wikidata.org/wiki/Q1937518","display_name":"Reservation","level":2,"score":0.8206242322921753},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8157943487167358},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.8082727193832397},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6972635984420776},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5191192030906677},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.5169800519943237},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.5065475702285767},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4959186017513275},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.48638394474983215},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4683857262134552},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.464380145072937},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41071105003356934},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.38626617193222046},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.33443108201026917},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3286401033401489},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.07773396372795105},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmc.2021.3123135","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2021.3123135","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Mobile Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7225915753","display_name":null,"funder_award_id":"61771312","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W2056163839","https://openalex.org/W2064675550","https://openalex.org/W2139837868","https://openalex.org/W2145339207","https://openalex.org/W2343140702","https://openalex.org/W2401610261","https://openalex.org/W2514431540","https://openalex.org/W2525400794","https://openalex.org/W2528639018","https://openalex.org/W2554427106","https://openalex.org/W2756203131","https://openalex.org/W2762588064","https://openalex.org/W2783772867","https://openalex.org/W2808417010","https://openalex.org/W2809740924","https://openalex.org/W2889540440","https://openalex.org/W2895688688","https://openalex.org/W2906622513","https://openalex.org/W2907834603","https://openalex.org/W2918334020","https://openalex.org/W2918335825","https://openalex.org/W2918400102","https://openalex.org/W2956452632","https://openalex.org/W2963549123","https://openalex.org/W2968424451","https://openalex.org/W2978510400","https://openalex.org/W2980360843","https://openalex.org/W2981618170","https://openalex.org/W2994053796","https://openalex.org/W2996667481","https://openalex.org/W2999446243","https://openalex.org/W3004589281","https://openalex.org/W3082239611","https://openalex.org/W3103720336","https://openalex.org/W3105066943","https://openalex.org/W3133281398","https://openalex.org/W3154030744","https://openalex.org/W3170708168","https://openalex.org/W4394672593","https://openalex.org/W6628877408","https://openalex.org/W6678200026","https://openalex.org/W6683195989","https://openalex.org/W6684921986","https://openalex.org/W6864350279"],"related_works":["https://openalex.org/W3154796165","https://openalex.org/W4322761281","https://openalex.org/W4238233472","https://openalex.org/W4313463218","https://openalex.org/W4312996489","https://openalex.org/W3111395152","https://openalex.org/W4313526662","https://openalex.org/W3106131444","https://openalex.org/W3216099748","https://openalex.org/W4205963435"],"abstract_inverted_index":{"Edge":[0],"computing":[1],"is":[2,19,71,84,99,111,152,173,185],"promising":[3],"for":[4,13,49,180],"connected":[5,50],"vehicles.":[6],"As":[7],"vehicles":[8],"move,":[9],"their":[10],"resource":[11,41,124,133],"demands":[12,42,76],"edge":[14,23],"servers":[15,24],"vary.":[16],"Thus,":[17,135],"it":[18,196],"necessary":[20],"to":[21,26,43,58,73,119,145,154,175],"reserve":[22],"dynamically":[25],"meet":[27],"variable":[28,75],"demands.":[29,60,134,147],"Existing":[30],"schemes":[31,54],"of":[32,40,93,123,132],"edge-server":[33,80],"reservation":[34,141],"usually":[35],"rely":[36],"on":[37,86,190],"statistical":[38],"information":[39],"make":[44],"reservations;":[45],"they":[46],"are":[47,55],"infeasible":[48],"vehicles,":[51],"since":[52],"such":[53],"not":[56],"adaptive":[57],"time-varying":[59],"To":[61],"this":[62],"end,":[63],"a":[64,114,168],"spatio-temporal":[65,121,165],"reinforcement":[66,95],"learning":[67,96],"scheme":[68],"called":[69,171],"DeepReserve":[70,184],"developed":[72],"learn":[74],"and":[77],"then":[78],"conduct":[79],"reservation.":[81],"Its":[82],"design":[83],"based":[85],"the":[87,105,129,136,156,160,164,177],"deep":[88,94],"deterministic":[89],"policy":[90],"gradient":[91],"algorithm":[92],"(DRL),":[97],"but":[98],"featured":[100],"with":[101],"several":[102],"enhancements.":[103],"First,":[104],"fully-connected":[106],"neural":[107,161],"network":[108,118,162],"in":[109,138],"DRL":[110,139],"replaced":[112],"by":[113,159],"convolutional":[115],"LSTM":[116],"(ConvLSTM)":[117],"extract":[120],"features":[122],"demands,":[125],"which":[126],"highly":[127],"improves":[128],"prediction":[130],"accuracy":[131],"actions":[137,157],"(i.e.,":[140],"decisions)":[142],"can":[143],"adapt":[144],"future":[146],"Second,":[148],"an":[149],"action":[150],"amender":[151],"designed":[153,174],"ensure":[155],"selected":[158],"follow":[163],"correlation.":[166],"Finally,":[167],"training":[169,178],"method":[170],"DR-Train":[172],"stabilize":[176],"procedure":[179],"different":[181],"traffic":[182],"patterns.":[183],"evaluated":[186],"through":[187],"extensive":[188],"experiments":[189],"real-world":[191],"datasets.":[192],"Results":[193],"show":[194],"that":[195],"outperforms":[197],"state-of-the-art":[198],"approaches.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}