{"title":"Connectivity management to support reliable communication on Cognitive vehicular networks","authors":"Cláudio Silva, E. Cerqueira, M. N. Lima","doi":"10.1109/WD.2014.7020839","DOIUrl":null,"url":null,"abstract":"Applications related to driving safety, mobile health, and entertainment present communication constraints, requiring reliability in data delivery. Ensuring reliability in highly dynamic vehicular networks is a demanding task due to fast variations on connectivity and network conditions. This paper presents MOCA, a Mechanism for cOnnectivity management on Cognitive vehiculAr networks. MOCA benefits from the flexibility provided by the cognitive radio technology, accessing opportunistically the frequency spectrum. Also, it manages the use of frequency channels based on information from vehicles, such as speed and driving direction; and on the application requirements. The proposed mechanism is rigorously tested on urban scenarios and compared to one representative approach from the literature. Evaluation results demonstrate that MOCA improves significantly connectivity in vehicular cognitive networks and outperforms the compared approach on throughput and jitter.","PeriodicalId":311349,"journal":{"name":"2014 IFIP Wireless Days (WD)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IFIP Wireless Days (WD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WD.2014.7020839","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Applications related to driving safety, mobile health, and entertainment present communication constraints, requiring reliability in data delivery. Ensuring reliability in highly dynamic vehicular networks is a demanding task due to fast variations on connectivity and network conditions. This paper presents MOCA, a Mechanism for cOnnectivity management on Cognitive vehiculAr networks. MOCA benefits from the flexibility provided by the cognitive radio technology, accessing opportunistically the frequency spectrum. Also, it manages the use of frequency channels based on information from vehicles, such as speed and driving direction; and on the application requirements. The proposed mechanism is rigorously tested on urban scenarios and compared to one representative approach from the literature. Evaluation results demonstrate that MOCA improves significantly connectivity in vehicular cognitive networks and outperforms the compared approach on throughput and jitter.