$\pi$-ROAD: a Learn-as-You-Go Framework for On-Demand Emergency Slices in V2X Scenarios

• URL: http://arxiv.org/abs/2012.06208v1
• Date: Fri, 11 Dec 2020 09:35:55 GMT
• Title: $\pi$-ROAD: a Learn-as-You-Go Framework for On-Demand Emergency Slices in V2X Scenarios
• Authors: Armin Okic, Lanfranco Zanzi, Vincenzo Sciancalepore, Alessandro Redondi, Xavier Costa-Perez
• Abstract summary: $pi$-ROAD is a framework to automatically learn regular mobile traffic patterns along roads, detect non-recurring events and classify them by level severity. Our results show that $pi$-ROAD successfully detects and classifies non-recurring road events and reduces up to $30%$ the impact of ENS on already running services.
• Score: 68.33556559127011
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Vehicle-to-everything (V2X) is expected to become one of the main drivers of 5G business in the near future. Dedicated \emph{network slices} are envisioned to satisfy the stringent requirements of advanced V2X services, such as autonomous driving, aimed at drastically reducing road casualties. However, as V2X services become more mission-critical, new solutions need to be devised to guarantee their successful service delivery even in exceptional situations, e.g. road accidents, congestion, etc. In this context, we propose $\pi$-ROAD, a \emph{deep learning} framework to automatically learn regular mobile traffic patterns along roads, detect non-recurring events and classify them by severity level. $\pi$-ROAD enables operators to \emph{proactively} instantiate dedicated \emph{Emergency Network Slices (ENS)} as needed while re-dimensioning the existing slices according to their service criticality level. Our framework is validated by means of real mobile network traces collected within $400~km$ of a highway in Europe and augmented with publicly available information on related road events. Our results show that $\pi$-ROAD successfully detects and classifies non-recurring road events and reduces up to $30\%$ the impact of ENS on already running services.

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