{"id":"https://openalex.org/W4315605995","doi":"https://doi.org/10.1109/tvt.2023.3235946","title":"A Reinforcement Learning Framework for Vehicular Network Routing Under Peak and Average Constraints","display_name":"A Reinforcement Learning Framework for Vehicular Network Routing Under Peak and Average Constraints","publication_year":2023,"publication_date":"2023-01-11","ids":{"openalex":"https://openalex.org/W4315605995","doi":"https://doi.org/10.1109/tvt.2023.3235946"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2023.3235946","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2023.3235946","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Vehicular Technology","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/A5101727539","display_name":"Nan Geng","orcid":"https://orcid.org/0009-0008-5760-3423"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nan Geng","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075904309","display_name":"Qinbo Bai","orcid":"https://orcid.org/0000-0003-2933-1180"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qinbo Bai","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103252154","display_name":"Chenyi Liu","orcid":"https://orcid.org/0000-0003-2630-4558"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyi Liu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018464968","display_name":"Tian Lan","orcid":"https://orcid.org/0000-0003-3010-8090"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tian Lan","raw_affiliation_strings":["George Washington University, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"George Washington University, Washington, DC, USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064822688","display_name":"Vaneet Aggarwal","orcid":"https://orcid.org/0000-0001-9131-4723"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vaneet Aggarwal","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101579014","display_name":"Yuan Yang","orcid":"https://orcid.org/0000-0002-3481-8447"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Yang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100771111","display_name":"Mingwei Xu","orcid":"https://orcid.org/0000-0002-4847-4585"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingwei Xu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101727539"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":3.3667,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.92322246,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"72","issue":"5","first_page":"6753","last_page":"6764"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10524","display_name":"Traffic control and management","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9991000294685364,"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/T12546","display_name":"Smart Parking Systems Research","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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":0.724503755569458},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6816280484199524},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.6693941354751587},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.556363582611084},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.5405565500259399},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5243497490882874},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.4980292320251465},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.48495009541511536},{"id":"https://openalex.org/keywords/static-routing","display_name":"Static routing","score":0.46922311186790466},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.4558590054512024},{"id":"https://openalex.org/keywords/network-performance","display_name":"Network performance","score":0.4263337254524231},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.3831067681312561},{"id":"https://openalex.org/keywords/routing-protocol","display_name":"Routing protocol","score":0.3649061918258667},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3611867427825928},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3267122507095337},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1408189833164215},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.13062313199043274}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.724503755569458},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6816280484199524},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.6693941354751587},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.556363582611084},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.5405565500259399},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5243497490882874},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4980292320251465},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.48495009541511536},{"id":"https://openalex.org/C204948658","wikidata":"https://www.wikidata.org/wiki/Q1119410","display_name":"Static routing","level":4,"score":0.46922311186790466},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.4558590054512024},{"id":"https://openalex.org/C203274722","wikidata":"https://www.wikidata.org/wiki/Q7001161","display_name":"Network performance","level":2,"score":0.4263337254524231},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.3831067681312561},{"id":"https://openalex.org/C104954878","wikidata":"https://www.wikidata.org/wiki/Q1648707","display_name":"Routing protocol","level":3,"score":0.3649061918258667},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3611867427825928},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3267122507095337},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1408189833164215},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.13062313199043274},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2023.3235946","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2023.3235946","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.49000000953674316}],"awards":[{"id":"https://openalex.org/G7488493096","display_name":null,"funder_award_id":"62221003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7675662412","display_name":null,"funder_award_id":"61832013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7888387042","display_name":null,"funder_award_id":"62132004","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":44,"referenced_works":["https://openalex.org/W1506085041","https://openalex.org/W2003151772","https://openalex.org/W2005325789","https://openalex.org/W2021669721","https://openalex.org/W2035428210","https://openalex.org/W2060617892","https://openalex.org/W2067747711","https://openalex.org/W2122011919","https://openalex.org/W2157075605","https://openalex.org/W2162595576","https://openalex.org/W2414564754","https://openalex.org/W2443552644","https://openalex.org/W2472493131","https://openalex.org/W2514619461","https://openalex.org/W2522153945","https://openalex.org/W2540923637","https://openalex.org/W2561208905","https://openalex.org/W2594892208","https://openalex.org/W2610198998","https://openalex.org/W2625483604","https://openalex.org/W2702886553","https://openalex.org/W2728471704","https://openalex.org/W2788654254","https://openalex.org/W2912960479","https://openalex.org/W2913285221","https://openalex.org/W2918377217","https://openalex.org/W2963000651","https://openalex.org/W2963856199","https://openalex.org/W2968239250","https://openalex.org/W2972619860","https://openalex.org/W2996776714","https://openalex.org/W3105078367","https://openalex.org/W3119743239","https://openalex.org/W3126443052","https://openalex.org/W3158548275","https://openalex.org/W3200353301","https://openalex.org/W4294562617","https://openalex.org/W4382239124","https://openalex.org/W6748271221","https://openalex.org/W6751535212","https://openalex.org/W6758773047","https://openalex.org/W6790285687","https://openalex.org/W6794639795","https://openalex.org/W6850279416"],"related_works":["https://openalex.org/W4213214852","https://openalex.org/W1589140671","https://openalex.org/W2512014291","https://openalex.org/W2904076065","https://openalex.org/W2465145931","https://openalex.org/W2120406836","https://openalex.org/W3201878770","https://openalex.org/W187740018","https://openalex.org/W2162286586","https://openalex.org/W4255368532"],"abstract_inverted_index":{"Providing":[0],"provable":[1],"performance":[2],"guarantees":[3],"in":[4,19,41,63,222,228,231],"vehicular":[5,107,194],"network":[6,27,42,61,108,195],"routing":[7,62,112,121,196],"problems":[8,197],"is":[9,123],"crucial":[10],"to":[11,193],"ensure":[12],"safely":[13],"and":[14,29,71,83,117,131,164,201,236],"timely":[15],"delivery":[16],"of":[17,148,172,233],"information":[18],"an":[20,134,156],"environment":[21],"characterized":[22],"by":[23,155],"high":[24],"mobility,":[25],"dynamic":[26],"conditions,":[28],"frequent":[30],"topology":[31],"changes.":[32],"While":[33],"Reinforcement":[34],"Learning":[35],"(RL)":[36],"has":[37],"shown":[38],"great":[39],"promise":[40],"routing,":[43,109],"existing":[44],"RL-based":[45,106],"solutions":[46],"typically":[47],"support":[48],"decision-making":[49],"with":[50,218],"either":[51],"peak":[52,74,118,163,200,235],"constraints":[53,75,85],"or":[54,79,90],"average":[55,84,87,116,165,202,223,237],"constraints,":[56,204],"but":[57],"not":[58],"both.":[59],"For":[60],"intelligent":[64],"transportation,":[65],"such":[66],"as":[67,125],"advanced":[68],"vehicle":[69],"control":[70],"safety,":[72],"both":[73,115,162,199,234],"(e.g.,":[76,86],"maximum":[77],"latency":[78,166,203],"minimum":[80],"bandwidth":[81],"guarantees)":[82],"transmit":[88],"power":[89],"data":[91],"rate":[92],"constraints)":[93],"must":[94],"be":[95,153],"satisfied.":[96],"In":[97],"this":[98],"paper,":[99],"we":[100,175],"propose":[101],"a":[102,126,149,180,184],"holistic":[103],"framework":[104],"for":[105],"which":[110],"maximizes":[111],"decisions":[113],"under":[114,198],"constraints.":[119,167,238],"The":[120],"problem":[122],"modeled":[124],"Constrained":[127],"Markov":[128],"Decision":[129],"Process":[130],"recast":[132],"into":[133,179],"optimization":[135],"based":[136],"on":[137],"Constraint":[138],"Satisfaction":[139],"Problems":[140],"(CSPs).":[141],"We":[142],"prove":[143],"that":[144,208],"the":[145,170,189],"optimal":[146],"policy":[147],"given":[150],"CSP":[151],"can":[152],"learned":[154],"extended":[157],"Q-learning":[158],"algorithm":[159,192,210],"while":[160,226],"satisfying":[161],"To":[168],"improve":[169],"scalability":[171],"our":[173,209],"framework,":[174],"further":[176],"turn":[177],"it":[178],"decentralized":[181],"implementation":[182],"through":[183],"cluster-based":[185],"learning":[186],"structure.":[187],"Applying":[188],"proposed":[190],"RL":[191],"simulation":[205],"results":[206],"show":[207],"achieves":[211],"much":[212],"higher":[213],"rewards":[214],"than":[215],"heuristic":[216],"baselines":[217],"over":[219],"40%":[220],"improvement":[221],"transmission":[224],"rate,":[225],"resulting":[227],"zero":[229],"violation":[230],"terms":[232]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}