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Multimodal Named Data Discovery With Interest Broadcast Suppression for Vehicular CPS

机译:具有兴趣广播抑制车辆CP的多模式命名数据发现

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摘要

Cyber-physical system (CPS) provides a well-organized integration between communication, computation, and control (3C) technologies. CPS has been widely used in the vehicular networks and it requires to discover multimodal data from the physical system to make appropriate decisions and actions, for example, congestion warnings, applying brakes, adjusting speed limits, etc. Information discovery and availability at individual network elements is one of the fundamental foundations of CPS. In this paper, we proposed two multimodal network information discovery schemes for vehicular CPS using the Named Data Networking (NDN). One of the proposed schemes simply modifies the pull-based NDN communication mechanism to discover multimodal multi-hop data from the network and the other scheme uses the Interest broadcast suppression (IBS) mechanism. The proposed Interest broadcast suppression scheme adapts the holding time technique to defer the Interest forwarding and its computation involves the hop-count, distance, and other network parameters. Simulation results show that the proposed schemes discover about 172 and 162 percent more multimodal information from approximately 283 and 210 percent more network area by suppressing approximately 50 percent of the Interest broadcast storm in highway and the urban traffic scenarios, respectively.
机译:网络物理系统(CPS)提供了通信,计算和控制(3C)技术之间的良好组织集成。 CPS已广泛用于车辆网络中,它需要发现来自物理系统的多模式数据,以制定适当的决策和动作,例如拥塞警告,应用刹车,调整速度限制等。信息发现和各个网络元素的信息发现和可用性是CPS的基本基础之一。在本文中,我们提出了使用命名数据网络(NDN)的两个多模式网络信息发现车辆CPS。其中一个提出的方案只是修改基于拉动的NDN通信机制,以发现来自网络的多模式多跳数据,而其他方案使用兴趣广播抑制(IBS)机制。所提出的兴趣广播抑制方案适应保持时间技术,以推迟利息转发,其计算涉及跳数,距离和其他网络参数。仿真结果表明,建议的方案通过抑制公路和城市交通方案的约50%的利息广播风暴,从大约283和210%的网络区域发现大约172和162%的多峰信息。

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