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Communication Dans Un Congrès Année : 2023

Intelligent reflecting surface aided vehicular edge computing

Résumé

Due to the rapid increase of connected devices and network traffic, the data transport from end-user devices to destination (connected device, cloud, edge servers, etc) can be interrupted because of obstacles and problems. In this paper, we propose to integrate edge servers with the intelligent reflecting surface (IRS) in a vehicular edge computing (VEC) environment. The IRS is deployed in fixed places inside the city (fixed IRS-Edge Nodes) and in taxis and buses (mobile IRS-Edge Nodes), where it is used for both reflecting signals and executing the different client vehicles' tasks. We propose an Optimal IRS-Edge Selection (OIES) model to select the optimal IRS-Edge Node(s) that satisfy the client vehicles' requirements. Moreover, we propose an Efficient IRS-Edge Selection (EIES) algorithm to deal with the high number of client vehicles in dense networks. The numerical results demonstrate the efficiency and the feasibility of the proposed solution.
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Dates et versions

hal-04173982 , version 1 (31-07-2023)

Identifiants

Citer

Mohammed Laroui, Hassine Moungla, Hossam Afifi, Mohamed Selim, Ahmed Kamal. Intelligent reflecting surface aided vehicular edge computing. IEEE Global Communications Conference (GLOBECOM), IEEE, Dec 2022, Rio de Janeiro, Brazil. pp.5577-5582, ⟨10.1109/GLOBECOM48099.2022.10000899⟩. ⟨hal-04173982⟩
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