Geymerson S. Ramos, Razvan Stanica, Rian G. S. Pinheiro, Andre L. L. Aquino
{"title":"Optimizing Vehicular Users Association in Urban Mobile Networks","authors":"Geymerson S. Ramos, Razvan Stanica, Rian G. S. Pinheiro, Andre L. L. Aquino","doi":"arxiv-2409.05845","DOIUrl":null,"url":null,"abstract":"This study aims to optimize vehicular user association to base stations in a\nmobile network. We propose an efficient heuristic solution that considers the\nbase station average handover frequency, the channel quality indicator, and\nbandwidth capacity. We evaluate this solution using real-world base station\nlocations from S\\~ao Paulo, Brazil, and the SUMO mobility simulator. We compare\nour approach against a state of the art solution which uses route prediction,\nmaintaining or surpassing the provided quality of service with the same number\nof handover operations. Additionally, the proposed solution reduces the\nexecution time by more than 80\\% compared to an exact method, while achieving\noptimal solutions.","PeriodicalId":501280,"journal":{"name":"arXiv - CS - Networking and Internet Architecture","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Networking and Internet Architecture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.05845","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study aims to optimize vehicular user association to base stations in a
mobile network. We propose an efficient heuristic solution that considers the
base station average handover frequency, the channel quality indicator, and
bandwidth capacity. We evaluate this solution using real-world base station
locations from S\~ao Paulo, Brazil, and the SUMO mobility simulator. We compare
our approach against a state of the art solution which uses route prediction,
maintaining or surpassing the provided quality of service with the same number
of handover operations. Additionally, the proposed solution reduces the
execution time by more than 80\% compared to an exact method, while achieving
optimal solutions.