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Publication - Dr Ioannis Mavromatis

    Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs

    Citation

    Tassi, A, Mavromatis, I, Piechocki, R, Nix, A, Compton, C, Poole, T & Schuster, W, 2019, ‘Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs’. in: 2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings: VTC2019-Spring. Institute of Electrical and Electronics Engineers (IEEE)

    Abstract

    Future Connected and Automated Vehicles (CAVs) will be supervised by cloud-based systems overseeing the overall security and orchestrating traffic flows. Such systems rely on data collected from CAVs across the whole city operational area. This paper develops a Fog Computing-based infrastructure for future Intelligent Transportation Systems (ITSs) enabling an agile and reliable off-load of CAV data. Since CAVs are expected to generate large quantities of data, it is not feasible to assume data off-loading to be completed while a CAV is in the proximity of a single Road-Side Unit (RSU). CAVs are expected to be in the range of an RSU only for a limited amount of time, necessitating data reconciliation across different RSUs, if traditional approaches to data off-load were to be used. To this end, this paper proposes an agile Fog Computing infrastructure, which interconnects all the RSUs so that the data reconciliation is solved efficiently as a by-product of deploying the Random Linear Network Coding (RLNC) technique. Our numerical results confirm the feasibility of our solution and show its effectiveness when operated in a large-scale urban testbed.

    Full details in the University publications repository