Deploying V2X services has become a challenging task. This is mainly due to the fact that such services have strict latency requirements. To meet these requirements, one potential solution is adopting mobile edge computing (MEC). However, this presents new challenges including how to find a cost efficient placement that meets other requirements such as latency. In this work, the problem of cost-optimal V2X service placement (CO-VSP) in a distributed cloud/edge environment is formulated. Additionally, a cost-focused delay-aware V2X service placement (DA-VSP) heuristic algorithm is proposed. Simulation results show that both CO-VSP model and DA-VSP algorithm guarantee the QoS requirements of all such services and illustrates the trade-off between latency and deployment cost.

翻译：部署V2X服务已成为一项具有挑战性的任务,主要原因是这类服务有严格的延迟要求,为满足这些要求,一个潜在的解决办法是采用移动边缘计算(MEC),然而,这带来了新的挑战,包括如何找到符合诸如延迟等其他要求的成本效益高的安置办法;在这项工作中,提出了在分布式云层/前沿环境中提供成本最佳V2X服务的问题;此外,还提议了以成本为重点的延迟认识V2X服务(DA-VSP)超速算法(DA-VSP),模拟结果表明,CO-VSP模型和DA-VSP算法都保证了所有这些服务的QOS要求,并说明了延迟与部署成本之间的权衡。