{"id":"https://openalex.org/W4402941109","doi":"https://doi.org/10.1142/s021926592450018x","title":"Bayesian Learning of Optimal Utility Functions for Message Routing in Vehicular Ad Hoc Networks","display_name":"Bayesian Learning of Optimal Utility Functions for Message Routing in Vehicular Ad Hoc Networks","publication_year":2024,"publication_date":"2024-09-27","ids":{"openalex":"https://openalex.org/W4402941109","doi":"https://doi.org/10.1142/s021926592450018x"},"language":"en","primary_location":{"id":"doi:10.1142/s021926592450018x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021926592450018x","pdf_url":null,"source":{"id":"https://openalex.org/S63112013","display_name":"Journal of Interconnection Networks","issn_l":"0219-2659","issn":["0219-2659","1793-6713"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Interconnection Networks","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/A5111358089","display_name":"Tao Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Tao Tao","raw_affiliation_strings":["Information Science, Hiroshima University, Kagamiyama 1-4-1, Higashi-Hiroshima, Hiroshima 739-8527, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Science, Hiroshima University, Kagamiyama 1-4-1, Higashi-Hiroshima, Hiroshima 739-8527, Japan","institution_ids":["https://openalex.org/I113306721"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087923932","display_name":"Satoshi Fujita","orcid":"https://orcid.org/0000-0001-9412-7309"},"institutions":[{"id":"https://openalex.org/I113306721","display_name":"Hiroshima University","ror":"https://ror.org/03t78wx29","country_code":"JP","type":"education","lineage":["https://openalex.org/I113306721"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Satoshi Fujita","raw_affiliation_strings":["Information Science, Hiroshima University, Kagamiyama 1-4-1, Higashi-Hiroshima, Hiroshima 739-8527, Japan"],"raw_orcid":"https://orcid.org/0000-0001-9412-7309","affiliations":[{"raw_affiliation_string":"Information Science, Hiroshima University, Kagamiyama 1-4-1, Higashi-Hiroshima, Hiroshima 739-8527, Japan","institution_ids":["https://openalex.org/I113306721"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5111358089"],"corresponding_institution_ids":["https://openalex.org/I113306721"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13753209,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":"03","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.967199981212616,"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":0.967199981212616,"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/T11720","display_name":"Probability and Risk Models","score":0.9194999933242798,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9172999858856201,"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":0.7418025732040405},{"id":"https://openalex.org/keywords/wireless-ad-hoc-network","display_name":"Wireless ad hoc network","score":0.6519112586975098},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.5293163657188416},{"id":"https://openalex.org/keywords/vehicular-ad-hoc-network","display_name":"Vehicular ad hoc network","score":0.5063649415969849},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.4983820915222168},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.48390278220176697},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.4416036307811737},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22478151321411133},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08603361248970032},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.05883747339248657}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7418025732040405},{"id":"https://openalex.org/C94523657","wikidata":"https://www.wikidata.org/wiki/Q4085781","display_name":"Wireless ad hoc network","level":3,"score":0.6519112586975098},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.5293163657188416},{"id":"https://openalex.org/C192448918","wikidata":"https://www.wikidata.org/wiki/Q682677","display_name":"Vehicular ad hoc network","level":4,"score":0.5063649415969849},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.4983820915222168},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.48390278220176697},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.4416036307811737},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22478151321411133},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08603361248970032},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.05883747339248657}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s021926592450018x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021926592450018x","pdf_url":null,"source":{"id":"https://openalex.org/S63112013","display_name":"Journal of Interconnection Networks","issn_l":"0219-2659","issn":["0219-2659","1793-6713"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Interconnection Networks","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W54243723","https://openalex.org/W1982002312","https://openalex.org/W2006895189","https://openalex.org/W2010634640","https://openalex.org/W2015348867","https://openalex.org/W2021319127","https://openalex.org/W2026950899","https://openalex.org/W2039502893","https://openalex.org/W2040459121","https://openalex.org/W2054161023","https://openalex.org/W2057225534","https://openalex.org/W2078712199","https://openalex.org/W2096326441","https://openalex.org/W2104541072","https://openalex.org/W2117752968","https://openalex.org/W2125957038","https://openalex.org/W2127680972","https://openalex.org/W2129401896","https://openalex.org/W2133647312","https://openalex.org/W2135712710","https://openalex.org/W2139041219","https://openalex.org/W2144899618","https://openalex.org/W2167071526","https://openalex.org/W2337845997","https://openalex.org/W2564407152","https://openalex.org/W2769999641","https://openalex.org/W2790860712","https://openalex.org/W2892277620","https://openalex.org/W3000535985","https://openalex.org/W3002630244","https://openalex.org/W3048756053","https://openalex.org/W3135393902","https://openalex.org/W3160529500","https://openalex.org/W3188342159","https://openalex.org/W4205782402","https://openalex.org/W4210398069","https://openalex.org/W4236354166","https://openalex.org/W4312767306"],"related_works":["https://openalex.org/W2027636740","https://openalex.org/W2062688728","https://openalex.org/W2061231656","https://openalex.org/W2771454953","https://openalex.org/W3046762796","https://openalex.org/W3202102306","https://openalex.org/W3046260513","https://openalex.org/W2998294818","https://openalex.org/W45347327","https://openalex.org/W4327774248"],"abstract_inverted_index":{"This":[0],"paper":[1],"explores":[2],"the":[3,25,52,61,85,89,110,134,140,148,152,160,170],"application":[4],"of":[5,27,55,60,113,127],"machine":[6],"learning":[7,112],"techniques":[8],"for":[9],"acquiring":[10],"utility":[11,106,167],"functions":[12],"in":[13,32,151,176],"message":[14,28,80,86,178],"routing":[15,31,179],"within":[16,133],"Vehicular":[17],"Ad":[18],"Hoc":[19],"Networks":[20],"(VANETs),":[21],"aiming":[22],"to":[23,68,71,81,88,146,169],"enhance":[24,84],"performance":[26],"routing.":[29],"Message":[30],"VANETs":[33],"employs":[34],"a":[35,96],"store-carry-and-forward":[36],"protocol,":[37],"where":[38],"vehicles":[39],"(nodes)":[40],"holding":[41],"messages":[42,49,70,129],"traverse":[43],"suitable":[44],"trajectories":[45],"and":[46,137],"opportunistically":[47],"forward":[48,69],"upon":[50,99],"entering":[51],"communication":[53],"range":[54],"other":[56],"nodes.":[57],"The":[58],"core":[59],"protocols":[62],"involves":[63],"context-dependent":[64],"decision-making":[65],"on":[66,105,159],"whether":[67],"an":[72,131],"encountered":[73],"node":[74],"and,":[75],"if":[76],"so,":[77],"determining":[78],"which":[79],"transmit.":[82],"To":[83],"arrival":[87],"destination":[90,125],"with":[91],"short":[92],"delay,":[93],"we":[94],"introduce":[95],"method":[97,118,164],"building":[98],"Wu":[100],"et":[101],"al.\u2019s":[102],"prior":[103],"work":[104],"function":[107],"acquisition":[108],"through":[109],"structure":[111,153],"Bayesian":[114,135],"networks.":[115],"Our":[116],"proposed":[117],"incorporates":[119],"two":[120],"key":[121],"innovations:":[122],"(1)":[123],"integrating":[124],"information":[126],"forwarded":[128],"as":[130],"attribute":[132,149],"network":[136],"(2)":[138],"extending":[139],"crossover":[141],"operation":[142],"from":[143],"genetic":[144],"algorithms":[145],"optimize":[147],"order":[150],"learning.":[154],"Through":[155],"extensive":[156],"experiments":[157],"conducted":[158],"ONE":[161],"simulator,":[162],"our":[163],"demonstrates":[165],"superior":[166],"compared":[168],"existing":[171],"baselines,":[172],"showcasing":[173],"its":[174],"effectiveness":[175],"VANET":[177],"improvement.":[180]},"counts_by_year":[],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}