{"id":"https://openalex.org/W4388083388","doi":"https://doi.org/10.1109/pimrc56721.2023.10294053","title":"A Deep Reinforcement Learning Approach for Dependency-Aware Task Offloading in Cooperative Vehicular Networks","display_name":"A Deep Reinforcement Learning Approach for Dependency-Aware Task Offloading in Cooperative Vehicular Networks","publication_year":2023,"publication_date":"2023-09-05","ids":{"openalex":"https://openalex.org/W4388083388","doi":"https://doi.org/10.1109/pimrc56721.2023.10294053"},"language":"en","primary_location":{"id":"doi:10.1109/pimrc56721.2023.10294053","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc56721.2023.10294053","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","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/A5100998171","display_name":"Yixin Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yixin Fan","raw_affiliation_strings":["Xidian University,State Key Laboratory of Integrated Services Networks,Xi&#x2019;an,China,710071"],"affiliations":[{"raw_affiliation_string":"Xidian University,State Key Laboratory of Integrated Services Networks,Xi&#x2019;an,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038716780","display_name":"Xuelian Cai","orcid":"https://orcid.org/0000-0003-3352-9392"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuelian Cai","raw_affiliation_strings":["Xidian University,State Key Laboratory of Integrated Services Networks,Xi&#x2019;an,China,710071"],"affiliations":[{"raw_affiliation_string":"Xidian University,State Key Laboratory of Integrated Services Networks,Xi&#x2019;an,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034502293","display_name":"Wenwei Yue","orcid":"https://orcid.org/0000-0002-1890-5911"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenwei Yue","raw_affiliation_strings":["Xidian University,State Key Laboratory of Integrated Services Networks,Xi&#x2019;an,China,710071"],"affiliations":[{"raw_affiliation_string":"Xidian University,State Key Laboratory of Integrated Services Networks,Xi&#x2019;an,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115589603","display_name":"Jing Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Zheng","raw_affiliation_strings":["Xidian University,State Key Laboratory of Integrated Services Networks,Xi&#x2019;an,China,710071"],"affiliations":[{"raw_affiliation_string":"Xidian University,State Key Laboratory of Integrated Services Networks,Xi&#x2019;an,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015340798","display_name":"Changle Li","orcid":"https://orcid.org/0000-0003-2568-8908"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changle Li","raw_affiliation_strings":["Xidian University,State Key Laboratory of Integrated Services Networks,Xi&#x2019;an,China,710071"],"affiliations":[{"raw_affiliation_string":"Xidian University,State Key Laboratory of Integrated Services Networks,Xi&#x2019;an,China,710071","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100998171"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.206,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.52025622,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9951000213623047,"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":0.9951000213623047,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9908000230789185,"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"}},{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9793999791145325,"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":0.8838192224502563},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.859683632850647},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.8052465915679932},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.6599723100662231},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6050513386726379},{"id":"https://openalex.org/keywords/computation-offloading","display_name":"Computation offloading","score":0.5677791237831116},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5177642107009888},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.5175946950912476},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5075489282608032},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5073332190513611},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48856720328330994},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.46771612763404846},{"id":"https://openalex.org/keywords/vehicular-ad-hoc-network","display_name":"Vehicular ad hoc network","score":0.45562174916267395},{"id":"https://openalex.org/keywords/mobile-edge-computing","display_name":"Mobile edge computing","score":0.41821444034576416},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.40623706579208374},{"id":"https://openalex.org/keywords/wireless-ad-hoc-network","display_name":"Wireless ad hoc network","score":0.1235126256942749},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.11628696322441101},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07772612571716309}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8838192224502563},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.859683632850647},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.8052465915679932},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.6599723100662231},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6050513386726379},{"id":"https://openalex.org/C2781041963","wikidata":"https://www.wikidata.org/wiki/Q18348618","display_name":"Computation offloading","level":4,"score":0.5677791237831116},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5177642107009888},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.5175946950912476},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5075489282608032},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5073332190513611},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48856720328330994},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.46771612763404846},{"id":"https://openalex.org/C192448918","wikidata":"https://www.wikidata.org/wiki/Q682677","display_name":"Vehicular ad hoc network","level":4,"score":0.45562174916267395},{"id":"https://openalex.org/C2776061582","wikidata":"https://www.wikidata.org/wiki/Q25325231","display_name":"Mobile edge computing","level":3,"score":0.41821444034576416},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.40623706579208374},{"id":"https://openalex.org/C94523657","wikidata":"https://www.wikidata.org/wiki/Q4085781","display_name":"Wireless ad hoc network","level":3,"score":0.1235126256942749},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.11628696322441101},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07772612571716309},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pimrc56721.2023.10294053","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc56721.2023.10294053","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":15,"referenced_works":["https://openalex.org/W2767011558","https://openalex.org/W2797431058","https://openalex.org/W2910603649","https://openalex.org/W3004421451","https://openalex.org/W3013810395","https://openalex.org/W3030647508","https://openalex.org/W3046127806","https://openalex.org/W3109463546","https://openalex.org/W3133576474","https://openalex.org/W3203858545","https://openalex.org/W3204939877","https://openalex.org/W3217119770","https://openalex.org/W4285064947","https://openalex.org/W4289520433","https://openalex.org/W6801967661"],"related_works":["https://openalex.org/W4200420173","https://openalex.org/W3120617837","https://openalex.org/W3127808443","https://openalex.org/W2916011811","https://openalex.org/W3034137700","https://openalex.org/W4362496467","https://openalex.org/W2896883851","https://openalex.org/W2917127270","https://openalex.org/W3185499500","https://openalex.org/W2796352555"],"abstract_inverted_index":{"To":[0],"investigate":[1],"the":[2,40,48,57,63,69,78,84,91,118,123,134,141,145,150,156,161,178],"diversified":[3],"applications":[4],"in":[5,184],"vehicular":[6,14],"networks,":[7],"artificial":[8],"intelligence,":[9],"intelligent":[10],"edge":[11],"computing,":[12],"and":[13,132],"networks":[15],"are":[16],"combined.":[17],"By":[18],"offloading":[19,53,72,105,124,158,188],"computation":[20,79],"tasks":[21],"to":[22,25,38,68,87,139,154],"devices":[23],"close":[24],"vehicles,":[26],"Vehicular":[27],"Edge":[28],"Computing":[29],"(VEC)":[30],"has":[31,86],"emerged":[32],"as":[33,126],"a":[34,75,100],"new":[35],"computing":[36],"paradigm":[37],"tackle":[39],"problem.":[41],"Most":[42],"existing":[43,182],"VEC":[44],"methods":[45,183],"simply":[46],"slice":[47],"application":[49],"into":[50,115],"subtasks":[51],"for":[52,107],"purposes":[54],"without":[55],"considering":[56,173],"dependencies":[58,175],"between":[59],"subtasks.":[60],"In":[61,95],"practice,":[62],"dependency":[64,113],"information":[65],"is":[66,93],"critical":[67],"efficiency":[70],"of":[71,81,144],"strategies.":[73],"If":[74],"subtask":[76],"requires":[77],"result":[80],"another":[82],"subtask,":[83],"latter":[85],"be":[88],"processed":[89],"before":[90],"former":[92],"finished.":[94],"this":[96],"paper,":[97],"we":[98,121,148],"propose":[99],"deep":[101],"reinforcement":[102],"learning":[103],"based":[104],"strategy":[106,180],"multi-vehicle":[108],"collaboration":[109],"VEC,":[110],"with":[111],"task":[112,174,187],"taken":[114],"account.":[116],"With":[117],"proposed":[119,179],"strategy,":[120],"formulate":[122],"problem":[125],"an":[127],"Markov":[128],"Decision":[129],"Process":[130],"(MDP)":[131],"use":[133],"Sequence-to-Sequence":[135],"(S2S)":[136],"neural":[137,152],"network":[138,153],"represent":[140],"policy/value":[142],"function":[143],"MDP.":[146],"Furthermore,":[147],"train":[149],"S2S":[151],"obtain":[155],"appropriate":[157],"policy":[159],"using":[160],"Proximal":[162],"Policy":[163],"Optimization":[164],"(PPO)":[165],"technique.":[166],"Our":[167],"simulation":[168],"results":[169],"indicate":[170],"that,":[171],"by":[172],"during":[176],"offloading,":[177],"outperforms":[181],"effectively":[185],"reducing":[186],"latencies.":[189]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
