THE NEXT GENERATION VEHICULAR NETWORKS: A CONTENT-CENTRIC FRAMEWORK

THE NEXT GENERATION VEHICULAR NETWORKS: A CONTENT-CENTRIC FRAMEWORK
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DOI:
10.1109/mwc.2017.1600195wc
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发表时间:
2017-02-01
影响因子:
12.9
通讯作者:
Yang, Qing
Yang, Qing
中科院分区:
计算机科学1区
文献类型:
--
作者:
Su, Zhou;Hui, Yilong;Yang, Qing

文献摘要

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由于车辆规模的不断扩大和多媒体业务的新需求,当前车载网络面临着增加容量、支持移动性和提高QoE的挑战。基于以内容为中心的架构的新一代车载网络的创新设计已被提出。然而,该框架和相关算法的细节还没有得到充分的研究。在本文中,我们提出了一个以内容为中心的车辆网络(CCVN)的新框架。通过引入以内容为中心的单元,可以根据车辆的命名信息管理车辆之间交换的内容。车辆可以发送兴趣来获取想要的内容,而不是发送传统的信息请求。然后,我们提出了一种集成算法,借助以内容为中心的单元向车辆传递内容。内容可以根据车辆密度和内容受欢迎程度决定的优先级进行存储。根据传输率和网络拓扑的分析,更新未决利益。在车辆移动期间提供内容的以内容为中心的单元的位置由转发信息确定。最后,通过仿真实验验证了该框架的有效性。结果表明,所提出的框架优于现有的方法,能够更有效地交付内容。
Due to the expanding scale of vehicles and the new demands of multimedia services, current vehicular networks face challenges to increase capacity, support mobility, and improve QoE. An innovative design of next generation vehicular networks based on the content-centric architecture has been advocated recently. However, the details of the framework and related algorithms have not been sufficiently studied. In this article, we present a novel framework of a content-centric vehicular network (CCVN). By introducing a content-centric unit, contents exchanged between vehicles can be managed based on their naming information. Vehicles can send interests to obtain wanted contents instead of sending conventional information requests. Then we present an integrated algorithm to deliver contents to vehicles with the help of content-centric units. Contents can be stored according to their priorities determined by vehicle density and content popularity. Pending interests are updated based on the analysis of transmission ratio and network topology. The location of a content-centric unit to provide content during the moving of vehicles is determined by the forwarding information. Finally, simulation experiments are carried out to show the efficiency of the proposed framework. Results indicate that the proposed framework outperforms the existing method and is able to deliver contents more efficiently.