Takamasa Higuchi, R. Onishi, O. Altintas, Daiki Nobayashi, T. Ikenaga, K. Tsukamoto
{"title":"Regional InfoHubs by vehicles: balancing spatio-temporal coverage and network load","authors":"Takamasa Higuchi, R. Onishi, O. Altintas, Daiki Nobayashi, T. Ikenaga, K. Tsukamoto","doi":"10.1145/2938681.2938688","DOIUrl":null,"url":null,"abstract":"The growing ubiquity of on-board wireless communication devices in vehicles is steadily opening up new possibilities of vehicular networks. In this paper, we design a framework to utilize radio-equipped cars as regional information hubs, which periodically disseminate public regional information (e.g., advertisements, travel tips, emergency info, etc.) over a designated geographical area in a city. The cars driving in the designated area repeatedly broadcast the data messages, allowing other drivers and pedestrians to passively obtain the information with their on-board wireless devices and/or smartphones. Although the idea follows a natural extension of the current capability of vehicular networks, vehicle densities in urban areas are typically highly non-uniform both in time and space, making it difficult to robustly disseminate data messages with minimal network load. We tackle this issue by introducing a probabilistic framework to intelligently adapt message dissemination strategy. Analyzing location broadcast messages, which are periodically exchanged among vehicles for safety applications, our protocol predicts future locations of neighboring radio-equipped vehicles and dynamically adjusts probability of message transmissions at each moment to suppress redundant network traffic. Simulation results show that our protocol can reduce the total amount of redundant message transmissions by up to 78%, while maintaining the spatio-temporal coverage of message dissemination.","PeriodicalId":106267,"journal":{"name":"IoV-VoI '16","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IoV-VoI '16","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2938681.2938688","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
The growing ubiquity of on-board wireless communication devices in vehicles is steadily opening up new possibilities of vehicular networks. In this paper, we design a framework to utilize radio-equipped cars as regional information hubs, which periodically disseminate public regional information (e.g., advertisements, travel tips, emergency info, etc.) over a designated geographical area in a city. The cars driving in the designated area repeatedly broadcast the data messages, allowing other drivers and pedestrians to passively obtain the information with their on-board wireless devices and/or smartphones. Although the idea follows a natural extension of the current capability of vehicular networks, vehicle densities in urban areas are typically highly non-uniform both in time and space, making it difficult to robustly disseminate data messages with minimal network load. We tackle this issue by introducing a probabilistic framework to intelligently adapt message dissemination strategy. Analyzing location broadcast messages, which are periodically exchanged among vehicles for safety applications, our protocol predicts future locations of neighboring radio-equipped vehicles and dynamically adjusts probability of message transmissions at each moment to suppress redundant network traffic. Simulation results show that our protocol can reduce the total amount of redundant message transmissions by up to 78%, while maintaining the spatio-temporal coverage of message dissemination.