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Message-sensing classified transmission scheme based on mobile edge computing in the Internet of Vehicles
Software: Practice and Experience ( IF 3.5 ) Pub Date : 2020-07-19 , DOI: 10.1002/spe.2843
Haitao Zhao 1 , Yinyang Zhu 1 , Jiawen Tang 1 , Zhe Han 1 , Gagangeet Singh Aujla 2, 3
Affiliation  

With the rapid development of intelligent transportation, vehicle terminals generate a large number of data messages that need to be processed in real time, and the required computing and storage resources far exceed the load capacity of vehicle terminals. Mobile edge computing enables data resources to be processed near device terminals, and provides low-latency and high-reliability computing services to meet the power and service quality requirements of terminal devices. Therefore, in order to achieve better data resource management, this paper introduces mobile edge computing technology, and mainly researches secure message transmission optimization algorithms based on mobile edge computing. Firstly, we prioritize secure messages through the analytic hierarchy process. This can guarantee that the most urgent messages get the highest transmission level. Secondly, we establish an optimal task offloading model of delay and energy loss by assigning different weight factors to delay and energy loss. The Lagrangian relaxation method is used to transform the nonconvex problem into a convex problem. We use greedy algorithm to solve the main problem. Finally, the vehicle transmits secure messages through the topology of the local network within its defined communication range. Performance evaluation results show that the scheme not only reduces the redundant transmission of messages, but also improves the performance of end-to-end delay and message deliver success ratio of secure messages.

中文翻译:

车联网中基于移动边缘计算的消息感知分类传输方案

随着智能交通的飞速发展,车载终端产生大量需要实时处理的数据报文,所需的计算和存储资源远远超过车载终端的负载能力。移动边缘计算使数据资源能够在设备终端附近进行处理,提供低时延、高可靠的计算服务,满足终端设备对电量和服务质量的要求。因此,为了实现更好的数据资源管理,本文引入移动边缘计算技术,主要研究基于移动边缘计算的安全消息传输优化算法。首先,我们通过层次分析过程对安全消息进行优先级排序。这样可以保证最紧急的消息得到最高的传输级别。其次,我们通过为延迟和能量损失分配不同的权重因子来建立延迟和能量损失的最优任务卸载模型。拉格朗日松弛法用于将非凸问题转化为凸问题。我们使用贪心算法来解决主要问题。最后,车辆通过其定义的通信范围内的本地网络拓扑传输安全消息。性能评估结果表明,该方案不仅减少了消息的冗余传输,而且提高了安全消息的端到端延迟性能和消息传递成功率。我们通过为延迟和能量损失分配不同的权重因子来建立延迟和能量损失的最优任务卸载模型。拉格朗日松弛法用于将非凸问题转化为凸问题。我们使用贪心算法来解决主要问题。最后,车辆通过其定义的通信范围内的本地网络拓扑传输安全消息。性能评估结果表明,该方案不仅减少了消息的冗余传输,而且提高了安全消息的端到端延迟性能和消息传递成功率。我们通过为延迟和能量损失分配不同的权重因子来建立延迟和能量损失的最优任务卸载模型。拉格朗日松弛法用于将非凸问题转化为凸问题。我们使用贪心算法来解决主要问题。最后,车辆通过其定义的通信范围内的本地网络拓扑传输安全消息。性能评估结果表明,该方案不仅减少了消息的冗余传输,而且提高了安全消息的端到端延迟性能和消息传递成功率。车辆通过其定义的通信范围内的本地网络拓扑传输安全消息。性能评估结果表明,该方案不仅减少了消息的冗余传输,而且提高了安全消息的端到端延迟性能和消息传递成功率。车辆通过其定义的通信范围内的本地网络拓扑传输安全消息。性能评估结果表明,该方案不仅减少了消息的冗余传输,而且提高了安全消息的端到端延迟性能和消息传递成功率。
更新日期:2020-07-19
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