IoT and edge computing are profoundly changing the information era, bringing a hyper-connected and context-aware computing environment to reality. Connected vehicles are a critical outcome of this synergy, allowing for the seamless interconnection of autonomous mobile/fixed objects, giving rise to a decentralized vehicle-to-everything (V2X) paradigm. On this front, the European Telecommunications Standards Institute (ETSI) proposed the Multi-Access Edge Computing (MEC) standard, addressing the execution of cloud-like services at the very edge of the infrastructure, thus facilitating the support of low-latency services at the far-edge. In this article, we go a step further and propose a novel ETSI MEC-compliant architecture that fully exploits the synergies between the edge and far-edge, extending the pool of virtualized resources available at MEC nodes with vehicular ones found in the vicinity. In particular, our approach allows vehicle entities to access and partake in a negotiation process embodying a rewarding scheme, while addressing resource volatility as vehicles join and leave the resource pool. To demonstrate the viability and flexibility of our proposed approach, we have built an ETSI MEC-compliant simulation model, which could be tailored to distribute application requests based on the availability of both local and remote resources, managing their transparent migration and execution. In addition, the paper reports on the experimental validation of our proposal in a 5G network setting, contrasting different service delivery modes, by highlighting the potential of the dynamic exploitation of far-edge vehicular resources.

Feraudo A., Calvio A., Bujari A., Bellavista P. (2023). A Novel Design for Advanced 5G Deployment Environments with Virtualized Resources at Vehicular and MEC Nodes. 345 E 47TH ST, NEW YORK, NY 10017 USA : IEEE [10.1109/VNC57357.2023.10136327].

A Novel Design for Advanced 5G Deployment Environments with Virtualized Resources at Vehicular and MEC Nodes

Feraudo A.
Primo
;
Calvio A.
Secondo
;
Bujari A.;Bellavista P.
2023

Abstract

IoT and edge computing are profoundly changing the information era, bringing a hyper-connected and context-aware computing environment to reality. Connected vehicles are a critical outcome of this synergy, allowing for the seamless interconnection of autonomous mobile/fixed objects, giving rise to a decentralized vehicle-to-everything (V2X) paradigm. On this front, the European Telecommunications Standards Institute (ETSI) proposed the Multi-Access Edge Computing (MEC) standard, addressing the execution of cloud-like services at the very edge of the infrastructure, thus facilitating the support of low-latency services at the far-edge. In this article, we go a step further and propose a novel ETSI MEC-compliant architecture that fully exploits the synergies between the edge and far-edge, extending the pool of virtualized resources available at MEC nodes with vehicular ones found in the vicinity. In particular, our approach allows vehicle entities to access and partake in a negotiation process embodying a rewarding scheme, while addressing resource volatility as vehicles join and leave the resource pool. To demonstrate the viability and flexibility of our proposed approach, we have built an ETSI MEC-compliant simulation model, which could be tailored to distribute application requests based on the availability of both local and remote resources, managing their transparent migration and execution. In addition, the paper reports on the experimental validation of our proposal in a 5G network setting, contrasting different service delivery modes, by highlighting the potential of the dynamic exploitation of far-edge vehicular resources.
2023
2023 IEEE Vehicular Networking Conference (VNC)
97
103
Feraudo A., Calvio A., Bujari A., Bellavista P. (2023). A Novel Design for Advanced 5G Deployment Environments with Virtualized Resources at Vehicular and MEC Nodes. 345 E 47TH ST, NEW YORK, NY 10017 USA : IEEE [10.1109/VNC57357.2023.10136327].
Feraudo A.; Calvio A.; Bujari A.; Bellavista P.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/953701
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