认知车联网中道路感知基础设施辅助通信的移动自适应路由算法

M. Divyashree, H. G. Rangaraju, C. R. Revanna
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引用次数: 0

摘要

物联网(IoT)正在将传统车载 ad-hoc 网络(VANET)的功能扩展到车联网(IoV)。然而,为了提高 IoV 的智能性,还需要应对一些挑战,从而开发出一种名为认知车联网(CIoV)的不断发展的新技术。在本研究中,我们提出了一种道路感知基础设施辅助和车对车(V2V)自适应路由系统,用于选择最有效的路由,将数据从源头传输到目的地车辆,以减少数据传输延迟。使用 MATLAB 根据数据包交付率(PDR)、平均端到端(E2E)延迟和归一化路由开销对性能进行了测量和评估。通过将所提出的移动自适应路由算法(MARA)与现有协议进行比较,研究发现其性能优于现有协议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mobile Adaptive Routing Algorithm for Road-Aware Infrastructure-Assisted Communication in Cognitive Internet of Vehicles
The Internet of Things (IoT) is expanding the capabilities of traditional vehicular ad-hoc networks (VANET) into the Internet of Vehicles (IoV). However, there are a few challenges that need to be addressed in order to enhance the intelligence of IoV, leading to the development of a new evolving technology called Cognitive Internet of Vehicles (CIoV). In this study, we propose a road-aware infrastructure-assisted and vehicle-to-vehicle (V2V) adaptive routing system to select the most efficient route for delivering data from the source to the destination vehicle, with the aim of reducing data delivery delay. The performance is measured and evaluated based on packet delivery ratio (PDR), average end-to-end (E2E) delay, and normalised routing overhead using MATLAB. By comparing the proposed mobile adaptive routing algorithm (MARA) with existing protocols, it has been examined and found to outperform the existing ones in terms of performance.
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