车辆到基础设施通信中的流量预测辅助波长分配:基于光纤无线网络的框架

IF 5.8 2区 计算机科学 Q1 TELECOMMUNICATIONS
Akshita Gupta , Abhishek Pratap Singh , Arunima Srivastava , Vivek Ashok Bohara , Anand Srivastava , Martin Maier
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引用次数: 0

摘要

下一代互联和自动驾驶汽车的出现为用户和服务提供商提供了巨大的机遇。特别是,基于光纤无线(FiWi)的车辆到基础设施(V2I)网络可以满足第六代(6G)车辆网络的一些严格要求,包括更高的容量、更低的延迟和无处不在的连接。基于 FiWi 的 V2I 网络集成了下一代无源光网络 2(NG-PON2)和基于 IEEE 802.11p 的 V2I 网络。在这项工作中,我们首先回顾了各种车辆数据流量及其所需的关键性能指标(KPI),即吞吐量、延迟和可靠性。根据关键性能指标要求,V2I 流量被分为四类,并分配给光网络单元(ONU)的不同传输容器(T-CONT)。此外,为了最大限度地减少网络延迟,我们提出了一种基于机器学习(ML)的 T-CONT 优先级分配波长分配算法,可最大限度地减少 PON 中的波长切换实例数量。我们将所提出的基于 ML 的波长分配算法的性能与其他方法(即基于随机和相等 T-CONT 的波长分配算法)进行了比较。仿真结果表明,就端到端 (e2e) 时延、吞吐量和可靠性而言,所提算法比其他方法更高效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traffic prediction assisted wavelength allocation in vehicle-to-infrastructure communication: A fiber-wireless network based framework

The advent of the next generation of connected and autonomous cars offers immense opportunities for both users as well as service providers. In particular, fiber-wireless (FiWi) based vehicle-to-infrastructure (V2I) network can facilitate some of the stringent requirements of sixth-generation (6G) vehicular networks, including higher capacity, lower delay, and ubiquitous connectivity. FiWi based V2I network integrates the next generation passive optical network 2 (NG-PON2) with IEEE 802.11p based V2I network. In this work, we first review the various kinds of vehicular data traffic and their desired key performance indicators (KPIs), namely throughput, delay, and reliability. Depending on the KPI requirements, the V2I traffic is classified among four classes and assigned to different transmission containers (T-CONTs) of the optical network unit (ONU). Further, in order to minimize the delay of the network, we propose a machine learning (ML) based T-CONT priority assignment wavelength allocation algorithm that minimizes the number of wavelength switching instances in the PON. The performance of the proposed ML-based wavelength allocation algorithm is compared with the other approaches, namely random and equal T-CONT based wavelength allocation algorithms. Simulation results demonstrate the efficiency of the proposed algorithm vis-a-vis other approaches in terms of end-to-end (e2e) delay, throughput, and reliability.

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来源期刊
Vehicular Communications
Vehicular Communications Engineering-Electrical and Electronic Engineering
CiteScore
12.70
自引率
10.40%
发文量
88
审稿时长
62 days
期刊介绍: Vehicular communications is a growing area of communications between vehicles and including roadside communication infrastructure. Advances in wireless communications are making possible sharing of information through real time communications between vehicles and infrastructure. This has led to applications to increase safety of vehicles and communication between passengers and the Internet. Standardization efforts on vehicular communication are also underway to make vehicular transportation safer, greener and easier. The aim of the journal is to publish high quality peer–reviewed papers in the area of vehicular communications. The scope encompasses all types of communications involving vehicles, including vehicle–to–vehicle and vehicle–to–infrastructure. The scope includes (but not limited to) the following topics related to vehicular communications: Vehicle to vehicle and vehicle to infrastructure communications Channel modelling, modulating and coding Congestion Control and scalability issues Protocol design, testing and verification Routing in vehicular networks Security issues and countermeasures Deployment and field testing Reducing energy consumption and enhancing safety of vehicles Wireless in–car networks Data collection and dissemination methods Mobility and handover issues Safety and driver assistance applications UAV Underwater communications Autonomous cooperative driving Social networks Internet of vehicles Standardization of protocols.
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