Abstract

The relay-node selection plays a decisive impact on the message dissemination in vehicular network. However, in some scenarios, due to lack of the reliable and stable relay-node selection, the message dissemination suffers from an intolerable delay, even a failure. In this paper, we focus on a design of the robust relay selection, which aims at (1) achieving a maximum message dissemination speed in general scenarios, and (2) assuring an acceptable dissemination speed in the adverse scenario. Two adverse scenarios are first introduced for the message dissemination when the distance-based relay selection is applied in multi-hop broadcast. To tackle the challenge, we propose a robust distance-based relay selection by optimizing the exponent-based partitioning broadcast protocol (our previous work) and incorporating a proposed mini-black-burst-assisted mechanism. Moreover, we develop analytic models for the robust approach performances in terms of contention latency and packet delivery ratio (PDR). Simulations are used to verify these analytic models, demonstrate the acceptable performances of the proposal in adverse scenarios, and compare it with the state-of-the-art approaches in general scenarios. Results show an increase of more than 11.01% in terms of message dissemination speed independent of vehicle density and a stable PDR of more than 99.99%.

中文翻译：

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用于车辆网络中消息分发的基于距离的鲁棒中继选择

摘要

中继节点的选择对车载网络中的消息传播起着决定性的作用。但是，在某些情况下，由于缺乏可靠和稳定的中继节点选择，消息分发会遭受无法忍受的延迟，甚至失败。在本文中，我们专注于鲁棒中继选择的设计，其目的是（1）在一般情况下实现最大的消息传播速度，以及（2）在不利情况下确保可接受的传播速度。当在多跳广播中应用基于距离的中继选择时，首先引入了两种不利的情况来进行消息分发。为了应对挑战，我们通过优化基于指数的分区广播协议（我们之前的工作）并结合了建议的迷你黑场辅助机制，提出了一种基于距离的鲁棒中继选择。此外，我们针对争用延迟和数据包传送率（PDR）开发了用于鲁棒方法性能的分析模型。仿真用于验证这些分析模型，演示不利条件下建议的可接受性能，并将其与一般情况下的最新方法进行比较。结果表明，在不依赖车辆密度的情况下，消息的传播速度提高了11.01％以上，稳定的PDR超过99.99％。仿真用于验证这些分析模型，演示不利条件下建议的可接受性能，并将其与一般情况下的最新方法进行比较。结果表明，在不依赖车辆密度的情况下，消息的传播速度提高了11.01％以上，稳定的PDR超过99.99％。仿真用于验证这些分析模型，演示不利条件下建议的可接受性能，并将其与一般情况下的最新方法进行比较。结果表明，与车辆密度无关，消息的传播速度提高了11.01％以上，稳定的PDR超过99.99％。