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首页> 外文期刊>Communications, China >Mobile content distribution with vehicular cloud in urban VANETs
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Mobile content distribution with vehicular cloud in urban VANETs

机译:城市VANET中具有车载云的移动内容分发

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摘要

Plenty of multimedia contents such as traffic images, surveillance video, music and movie will flood into vehicular ad hoc networks. However, content distribution over VANETs is not a easy task, due to the high mobility of vehicles and intermittent connectivity. Infrastructure-based scheme can relieve the problem, but with a large amount of investment. In this paper, we propose a mobile content distribution scheme based on roadside parking cloud (RPC), which is formed by the parked car on the roadside, and mobile cloud (MC), which is formed by moving cars on the road. According to a trip history model, a mobile car can estimate its following trajectory. When it wants to download the content, gateway node of the RPC will work out a downloading schedule, which tells it how much chunks it can download from which RPCs. Moreover, the helper of the mobile car in mobile cloud would deliver specified chunks to it when there is lack of RPC in the following trip. Simulation results show that cloud-based scheme performs better than inter-vehicle communication approach and cluster-based scheme.
机译:交通图像,监视视频,音乐和电影等大量多媒体内容将涌入车载自组织网络。但是,由于车辆的高移动性和间歇性连接,通过VANET分发内容并不是一件容易的事。基于基础架构的方案可以缓解问题,但需要大量投资。在本文中,我们提出了一种基于路边停车云(RPC)和移动云(MC)的移动内容分发方案,该路边停车云由路边的停放的汽车组成,而移动云(MC)由路边的移动汽车组成。根据行程历史模型,移动汽车可以估计其跟随轨迹。当它想下载内容时,RPC的网关节点将制定一个下载时间表,告诉它可以从哪个RPC中下载多少块。此外,当在接下来的行程中缺少RPC时,移动云中移动汽车的助手将向其交付指定的块。仿真结果表明,基于云的方案比基于车辆的通信方法和基于集群的方案具有更好的性能。

著录项

  • 来源
    《Communications, China》 |2016年第8期|84-96|共13页
  • 作者单位

    School of Computer Science and Engineering, University of Electronic Science and Technology of China;

    Big Data Research Center of UESTC, University of Electronic Science and Technology of China;

    School of Computer Science and Engineering, University of Electronic Science and Technology of China;

    Hangzhou College of Commerce, Zhejiang Gongshang University;

    School of Computer Science and Engineering, University of Electronic Science and Technology of China;

    Big Data Research Center of UESTC, University of Electronic Science and Technology of China;

    School of Computer Science and Engineering, University of Electronic Science and Technology of China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Mobile communication; Automobiles; Roads; Trajectory; Logic gates; History;

    机译:移动通信;汽车;道路;轨迹;逻辑门;历史;

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