Resource Allocation in 5G IoV Architecture Based on SDN and Fog-Cloud Computing

TLDR

Traditional cloud‑based IoV architectures struggle to meet low‑latency ITS demands, while fog computing can reduce bandwidth bottlenecks and improve QoS but introduces complex network structures. The study aims to design an efficient 5G IoV architecture and resource‑allocation algorithm to manage heterogeneous computing resources and deliver high‑quality services. Based on fog‑cloud computing and SDN, the authors propose a novel 5G IoV architecture, construct a four‑objective model, and apply a many‑objective optimization algorithm to address service requirements. Experimental results show the proposed algorithm outperforms state‑of‑the‑art alternatives.

Abstract

In the traditional cloud-based Internet of Vehicles (IoV) architecture, it is difficult to guarantee the low latency requirements of the current intelligent transportation system (ITS). As a supplement to cloud computing, fog computing can effectively alleviate the bottlenecks of cloud computing bandwidth and computing resources and improve the quality of service (QoS) of the IoV. However, as a distributed system that operates near users, fog computing has a complicated network structure. In the complex and dynamic IoV environment, to effectively manage these computing resources with different attributes and provide high-quality services, it is necessary to design an efficient architecture and a resource allocation algorithm. Therefore, on the basis of fog-cloud computing and software-defined networking (SDN), a novel 5G IoV architecture is designed. In addition, after fully considering the service requirements of the IoV, a model of four objectives is constructed, and a many-objective optimization algorithm is proposed. The experiment results show that the proposed algorithm outperforms the other state-of-the-art algorithms.