-Ongoing-5G6GMECML/AITestbedVehicularPredictive allocation of edge computing resources for autonomous driving

Joint allocation of computing and radio resources based on blockchain for secure distributed processing of the complex applications for autonomous driving.

The project targets design and experimental verification of solutions for joint allocation of computing and mobile communication network resources for distributed processing of the complex applications composed of mutually dependent sub-tasks including those based on
neural networks. To guarantee reliability and availability of the resources on the time when these are required, we also consider pre-allocation (booking) of communication and computing resources in mid-term time horizon (dozens of second to hours) using blockchain.

 

Vehicular comunications, Edge computing, Radio resource management, Machine learning

Major results and publications

  • , , , , and
    Graph Neural Network Empowered Resource Allocation for Connected Autonomous Mobility
    IEEE Robotic Computing (IEEE IRC 2023), .

    [BibTex] [pdf]
  • , , , , , and
    Blockchain-based Route Selection with Allocation of Radio and Computing Resources for Connected Autonomous Vehicles
    IEEE Transactions on Intelligent Transportation Systems, volume 24, no. 7, .

    [BibTex] [pdf] [doi]

    Date:
    07/2022 - 06/2025
    Project No.:
    LUASK22064
    Funding:
    Ministry of Education, Youth and Sports
    Budget:
    ~125k EUR
    PI:
    Zdenek Becvar
    Team (6Gm):
    Pavel Mach, Shahzeb Javed
    Partners:
    TU Kosice (prof. Juraj Gazda)
    Topics:
    Communications, computation, resource allocation, prediction, distributed machine learning, autonomous driving

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