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Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs by Tassi, Andrea; Mavromatis, Ioannis; Piechocki, Robert; Nix, Andrew; Compton, Christian; Poole, Tracey; Schuster, Wolfgang is a scholarly article available to read on EtoBox.

What is Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs about?

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.

Author

Tassi, Andrea; Mavromatis, Ioannis; Piechocki, Robert; Nix, Andrew; Compton, Christian; Poole, Tracey; Schuster, Wolfgang

Published

2019

Language

EN