{"title":"TBD: Trajectory-Based Data Forwarding for Light-Traffic Vehicular Networks","authors":"J. Jeong, Shuo Guo, Yu Gu, T. He, D. Du","doi":"10.1109/ICDCS.2009.11","DOIUrl":null,"url":null,"abstract":"This paper proposes a Trajectory-Based Data Forwarding (TBD) scheme, tailored for the data forwarding in light- traffic vehicular ad-hoc networks. State-of-the-art schemes have demonstrated the effectiveness of their data forwarding strategies by exploiting known vehicular traffic statistics (e.g., densities and speeds) in these vehicular networks. These results are encouraging, however, further improvements can be made by taking advantage of the growing popularity of GPS-based navigation systems. This paper presents the first attempt to investigate how to effectively utilize vehicles\" trajectory information in a privacy-preserving manner. In our design, the trajectory information is combined with the traffic statistics to improve the performance of data forwarding in road networks. Through theoretical analysis and extensive simulation, it is shown that our design outperforms the existing scheme.","PeriodicalId":387968,"journal":{"name":"2009 29th IEEE International Conference on Distributed Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"106","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 29th IEEE International Conference on Distributed Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCS.2009.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 106
Abstract
This paper proposes a Trajectory-Based Data Forwarding (TBD) scheme, tailored for the data forwarding in light- traffic vehicular ad-hoc networks. State-of-the-art schemes have demonstrated the effectiveness of their data forwarding strategies by exploiting known vehicular traffic statistics (e.g., densities and speeds) in these vehicular networks. These results are encouraging, however, further improvements can be made by taking advantage of the growing popularity of GPS-based navigation systems. This paper presents the first attempt to investigate how to effectively utilize vehicles" trajectory information in a privacy-preserving manner. In our design, the trajectory information is combined with the traffic statistics to improve the performance of data forwarding in road networks. Through theoretical analysis and extensive simulation, it is shown that our design outperforms the existing scheme.