Connectivity management to support reliable communication on Cognitive vehicular networks

Cláudio Silva, E. Cerqueira, M. N. Lima
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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.
在认知车辆网络上支持可靠通信的连接管理
与驾驶安全、移动健康和娱乐相关的应用存在通信限制,需要数据传输的可靠性。由于连接性和网络条件的快速变化,确保高动态车辆网络的可靠性是一项艰巨的任务。提出了一种基于认知车辆网络的连通性管理机制MOCA。MOCA受益于认知无线电技术提供的灵活性,可以随意访问频谱。此外,它还根据车辆的信息(如速度和行驶方向)管理频率频道的使用;以及申请要求。提出的机制在城市场景中进行了严格的测试,并与文献中的一种代表性方法进行了比较。评估结果表明,MOCA算法显著提高了车辆认知网络的连通性,并且在吞吐量和抖动方面优于对比算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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