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.

翻译：物联网与边缘计算正在深刻改变信息时代，将超连接与情境感知计算环境变为现实。联网车辆是这一协同作用的关键成果，实现了自主移动/固定物体的无缝互联，催生了去中心化车联网（V2X）范式。在此背景下，欧洲电信标准化协会（ETSI）提出了多接入边缘计算（MEC）标准，旨在基础设施最边缘执行类云服务，从而支持远边缘的低延迟服务。本文进一步提出了一种符合ETSI MEC标准的新型架构，充分利用边缘与远边缘的协同效应，将MEC节点可用的虚拟化资源池扩展至周边车辆资源。具体而言，我们的方法允许车辆实体参与并接入包含奖励机制的协商过程，同时应对车辆加入和离开资源池时的资源波动性。为验证所提方法的可行性与灵活性，我们构建了符合ETSI MEC标准的仿真模型，该模型可根据本地与远程资源的可用性定制化分发应用请求，并实现其透明迁移与执行。此外，本文报告了在5G网络环境中对提案的实验验证，通过对比不同服务交付模式，突出了远边缘车辆资源动态利用的潜力。