{"id":"https://openalex.org/W4404034453","doi":"https://doi.org/10.1145/3666025.3699399","title":"Poster: Delay and Energy-Efficient Client Selection for Federated Learning in Vehicular Networks","display_name":"Poster: Delay and Energy-Efficient Client Selection for Federated Learning in Vehicular Networks","publication_year":2024,"publication_date":"2024-11-04","ids":{"openalex":"https://openalex.org/W4404034453","doi":"https://doi.org/10.1145/3666025.3699399"},"language":"en","primary_location":{"id":"doi:10.1145/3666025.3699399","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3666025.3699399","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3666025.3699399","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3666025.3699399","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019867090","display_name":"Junho Jeong","orcid":"https://orcid.org/0009-0008-5752-0855"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junho Jeong","raw_affiliation_strings":["Department of Computer Science and Engineering, Yonsei University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0008-5752-0855","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074207019","display_name":"Chang Kyung Kim","orcid":"https://orcid.org/0009-0008-3403-8302"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chang Kyung Kim","raw_affiliation_strings":["Department of Computer Science and Engineering, Yonsei University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0008-3403-8302","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101964277","display_name":"SuKyoung Lee","orcid":"https://orcid.org/0000-0002-3497-3295"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"SuKyoung Lee","raw_affiliation_strings":["Department of Computer Science and Engineering, Yonsei University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-3497-3295","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I193775966"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16358755,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"842","last_page":"843"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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":0.9962999820709229,"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/T10237","display_name":"Cryptography and Data Security","score":0.9929999709129333,"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":0.783711314201355},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6802261471748352},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.523680567741394},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.4446335434913635},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15194758772850037},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06509420275688171}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.783711314201355},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6802261471748352},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.523680567741394},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.4446335434913635},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15194758772850037},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06509420275688171},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3666025.3699399","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3666025.3699399","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3666025.3699399","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3666025.3699399","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3666025.3699399","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3666025.3699399","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8799999952316284}],"awards":[{"id":"https://openalex.org/G6082293287","display_name":null,"funder_award_id":"2022R1A2B5B01001683","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4404034453.pdf","grobid_xml":"https://content.openalex.org/works/W4404034453.grobid-xml"},"referenced_works_count":6,"referenced_works":["https://openalex.org/W3080934299","https://openalex.org/W3211199052","https://openalex.org/W4206236322","https://openalex.org/W4212984905","https://openalex.org/W4375928838","https://openalex.org/W4392158185"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3],"delay":[4,32,50],"and":[5,33,51,62,65],"energy-aware":[6],"clustering-based":[7],"client":[8],"selection":[9],"scheme":[10],"for":[11,28,58],"federated":[12],"learning":[13],"in":[14],"vehicular":[15],"networks.":[16],"We":[17],"propose":[18],"an":[19],"algorithm":[20,47],"that":[21,44],"selects":[22],"the":[23,45],"appropriate":[24],"number":[25],"of":[26],"vehicles":[27],"local":[29],"training,":[30],"minimizing":[31],"energy":[34,52],"consumption":[35,53],"while":[36],"ensuring":[37],"model":[38],"performance.":[39],"The":[40],"simulation":[41],"results":[42],"demonstrate":[43],"proposed":[46],"achieves":[48],"lower":[49],"compared":[54],"to":[55],"benchmark":[56],"methods,":[57],"both":[59],"IID":[60],"(independent":[61],"identically":[63],"distributed)":[64],"non-IID":[66],"datasets.":[67]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
