Publication:
A MEC-based Extended Virtual Sensing for Automotive Services

Loading...
Thumbnail Image
Identifiers
Publication date
2019-07-30
Defense date
Advisors
Tutors
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Impact
Google Scholar
Export
Research Projects
Organizational Units
Journal Issue
Abstract
Multi-access edge computing (MEC) comes with the promise of enabling low-latency applications and of reducing core network load by offloading traffic to edge service instances. Recent standardization efforts, among which the ETSI MEC, have brought about detailed architectures for the MEC. Leveraging the ETSI model, in this paper we first present a flexible, yet full-fledged, MEC architecture that is compliant with the standard specifications. We then use such architecture, along with the popular OpenAir Interface (OAI), for the support of automotive services with very tight latency requirements. We focus in particular on the Extended Virtual Sensing (EVS) services, which aim at enhancing the sensor measurements aboard vehicles with the data collected by the network infrastructure, and exploit this information to achieve better safety and improved passengers/driver comfort. For the sake of concreteness, we select the intersection control as an EVS service and present its design and implementation within the MEC platform. Experimental measurements obtained through our testbed show the excellent performance of the MEC EVS service against its equivalent cloud-based implementation, proving the need for MEC to support critical automotive services, as well as the benefits of the solution we designed.
Description
Keywords
Softwarized networks, Automotive services, Road safety, Multi-access edge computing, V2I communications
Bibliographic citation
Avino, G., Bande, P., Frangoudis, A., Vitale, C., Casetti, C., Chiasserini, C. F., ... Zennaro, G. (2019). A MEC-based Extended Virtual Sensing for Automotive Services. IEEE Transactions on Network and Service Management.