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Security-Aware Resource Allocation Scheme Based on DRL in Cloud–Edge–Terminal Cooperative Vehicular Network | IEEE Journals & Magazine | IEEE Xplore

Security-Aware Resource Allocation Scheme Based on DRL in Cloud–Edge–Terminal Cooperative Vehicular Network


Abstract:

Virtual network embedding (VNE) refers to the process of mapping virtual networks onto physical networks, which can improve the utilization and flexibility of network res...Show More

Abstract:

Virtual network embedding (VNE) refers to the process of mapping virtual networks onto physical networks, which can improve the utilization and flexibility of network resources. However, due to the complexity of VNE problems and the requirement for network security, how to efficiently complete VNE and ensure network security is important. In this article, we analyze the characteristics of the cloud–edge–terminal collaborative vehicular network and design a resource allocation mechanism based on VNEVNE, abbreviated as DRLS-VNE. First, we establish a multidimensional heterogeneous network model and design a five-layer neural network as the deep reinforcement learning (DRL) agent. The DRL agent can adaptively extract network feature attributes, thereby improving the performance of DRLS-VNE. Second, we introduce a dynamic trust evaluation mechanism, which can evaluate the trustworthiness of each node in the virtual network in real time and set embedding constraints based on the evaluation results. Finally, we conduct experiments to verify the practicality and effectiveness of DRLS-VNE. The experimental results show that our solution can significantly enhance the performance of the VNE solution.
Published in: IEEE Internet of Things Journal ( Volume: 11, Issue: 1, 01 January 2024)
Page(s): 95 - 104
Date of Publication: 07 July 2023

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