FOGO - an Optimized Fog and Edge Computing Method for VANETs

Vehicular Ad-hoc Networks (VANETs) have many specific issues and challenges due to a heterogeneous and highly dynamic environment, and therefore traditional solutions need to be improved and adopted in order to satisfy the networking and processing requirements. Fog and edge computing principles enable VANETs to achieve a more realistic and dependable architecture by using several layers for information processing. In this paper, the developed FOGO method is improved and customized for VANETs. The proposed solution is using an enhanced infrastructure in which additional mobile fog nodes are added to the network together with the existing stationary nodes. Small and medium sized messages are processed by mobile fog nodes, which then disseminate the results across the network. Roadside units (RSUs) are fixed, highly-capable devices positioned throughout the network to assist the processing of increasing volumes of data. Additionally, the cloud is taken into account, but only when processing large amounts of data. Along with the presented method flowcharts, operating algorithms, and message structure, the proposed system architecture is described. Furthermore, potential use cases are suggested together with the metrics for the system performance evaluation. The LuST scenario was used to evaluate the proposed architecture and the results showed improved message processing efficiency.