An efficient resource orchestration algorithm for enhancing throughput in fog computing-enabled vehicular networks

IF 5.8 2区计算机科学 Q1 TELECOMMUNICATIONS Vehicular Communications Pub Date : 2025-03-13 DOI:10.1016/j.vehcom.2025.100911

Md Asif Thanedar , Sanjaya Kumar Panda

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Abstract

The delay-sensitive applications, such as self-driving, smart transportation, navigation, and augmented reality assistance, can be evolved in vehicular ad-hoc networks (VANETs) using one of the leading paradigms, fog computing (FC). The intelligent vehicles are connected to the roadside infrastructure, such as high power nodes (HPNs) and roadside units (RSUs), also called fog nodes (FNs), for obtaining on-demand services. These FNs possess finite resources and can provide services to limited vehicles. However, when vehicles reach the network spike in demand, the FNs become impuissant in furnishing services in the existing solutions. As a result, there is a significant reduction in the network throughput. Therefore, we propose an efficient resource orchestration (ERO) algorithm to maximize the throughput by reducing the allocated resource blocks (RBs) of FNs. The ERO algorithm partitions the FN coverage region into restricted and non-restricted coverage regions. Then, it coordinates the RBs allocation among FNs by reducing RBs for the vehicles in the non-restricted coverage regions. This reduction is carried out by migrating RBs for offloading upstream services so that the overall occupied capacity of FNs is minimized. ERO constructs the minimum priority queue using the occupied capacity of FNs to perform optimal RBs migration between pairs of FNs. The ERO algorithm is evaluated, and simulation results show that the proposed algorithm performs better in terms of throughput, serviceability, availability, and service capability than existing algorithms.

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自动驾驶、智能交通、导航和增强现实辅助等对延迟敏感的应用，可以利用领先范例之一的雾计算（FC）在车载 ad-hoc 网络（VANET）中得到发展。智能车辆连接到路边基础设施，如高功率节点（HPN）和路边装置（RSU），也称为雾节点（FN），以获得按需服务。这些 FN 拥有有限的资源，可以为有限的车辆提供服务。然而，当车辆达到网络需求峰值时，现有解决方案中的 FN 在提供服务方面就会变得非常重要。因此，网络吞吐量大大降低。因此，我们提出了一种高效资源协调（ERO）算法，通过减少分配给 FN 的资源块（RB）来最大化吞吐量。ERO算法将 FN 覆盖区域划分为限制覆盖区域和非限制覆盖区域。然后，它通过减少非限制覆盖区域内车辆的 RB 来协调 FN 之间的 RB 分配。这种减少是通过迁移用于卸载上游服务的 RB 来实现的，从而使 FN 的总体占用容量最小。ERO利用FN的占用容量构建最小优先队列，在成对的FN之间执行最佳RB迁移。对ERO算法进行了评估，仿真结果表明，所提出的算法在吞吐量、服务性、可用性和服务能力方面都优于现有算法。

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来源期刊

Vehicular Communications Engineering-Electrical and Electronic Engineering

CiteScore

12.70

自引率

10.40%

发文量

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.