Improving Data Consistency in Vehicular Micro Clouds

In the field of vehicular networks, multiple approaches have been proposed to share and reuse data acquired by participating hosts. In this context, vehicular micro clouds extend the concept of Mobile Edge Computing (MEC) and bring data storage and processing to the vehicles, solving application tasks that need to be done in real-time. A critical point in shared computing tasks and storage is to keep all nodes synchronized and to maintain consistency. For the first time, we study the relevance of data versions in micro clouds offering intersection management service at four-way stop intersections and we investigate how different versions of data affect both road traffic and wireless communications. Our results validate the intuition that an increase in the amount of different data versions in the micro cloud has negative effects on both road traffic and wireless channel usage. Yet, the choice of the data sharing algorithm can make a huge difference and reduce these effects on a large scale. We found that synchronicity of data versions can be increased by up to 20% through small changes, e.g., keeping small amounts of data history in the applied algorithm.