As a worldwide pandemic, the coronavirus disease-19 (COVID-19) has caused serious restrictions in people's social life, along with the loss of lives, the collapse of economies and the disruption of humanitarian aids. Despite the advance of technological developments, we, as researchers, have witnessed that several issues need further investigation for a better response to a pandemic outbreak. Therefore, researchers recently started developing ideas to stop or at least reduce the spread of the pandemic. While there have been some prior works on wireless networks for combating a pandemic scenario, vehicular networks and their potential bottlenecks have not yet been fully examined. Furthermore, the vehicular scenarios can be identified as the locations, where the social distancing is mostly violated. With this motivation, this article provides an extensive discussion on vehicular networking for combating a pandemic. We provide the major applications of vehicular networking for combating COVID-19 in public transportation, in-vehicle diagnosis, border patrol and social distance monitoring. Next, we identify the unique characteristics of the collected data in terms of privacy, flexibility and coverage, then highlight corresponding future directions in privacy preservation, resource allocation, data caching and data routing. We believe that this work paves the way for the development of new products and algorithms that can facilitate the social life and help controlling the spread of the pandemic.
翻译:作为全球范围的流行病,Corona病毒19(COVID-19)对人们的社会生活造成严重限制,造成生命损失、经济崩溃和人道主义援助中断。尽管技术进步取得了进展,我们作为研究人员已经看到,有几个问题需要进一步调查,以更好地应对大流行病的爆发,因此,研究人员最近开始提出停止或至少减少该大流行病蔓延的想法。虽然以前曾就无线网络进行过一些工作,以防止大流行病的蔓延,但车辆网络及其潜在的瓶颈尚未得到充分研究。此外,车辆的情景可以被确定为主要破坏社会动荡的地点。这一文章以这一动机广泛讨论了为防治大流行病建立网络的问题。我们提供了在公共交通、车辆诊断、边境巡逻和社会距离监测方面打击CoVID-19的主要应用。我们随后从隐私、灵活性和覆盖面方面确定了所收集的数据的独特特点,然后强调了今后在隐私保护、资源分配、数据采集和数据传播方面的相应方向,从而帮助了大流行病的发展,从而推动了社会动态的发展和数据流传动。我们相信,这种发展的方式可以促进社会动态的发展和数据流传。