Research Institute for Computer and Information Communication, Chungbuk National University, Cheongju 28644, Republic of Korea.
Hyundai Autoever, Seoul 06179, Republic of Korea.
Sensors (Basel). 2023 Jun 21;23(13):5800. doi: 10.3390/s23135800.
In vehicular networks, vehicles download vehicular information for various applications, including safety, convenience, entertainment, and social interaction, from the corresponding content servers via stationary roadside units. Since sufficient RSUs might be difficult to deploy due to rough geographical conditions or high deployment costs, vehicular networks can feature uncovered outage zones between two neighboring RSUs. In these outage zones, vehicles cannot download content, and thus the vehicle networks are defined as intermittently connected vehicular networks. In intermittently connected vehicular networks, the download delay and traffic overhead on the backhaul links are increased due to the large size of the content requested by vehicle users and the long distances between RSUs. Using the mobility information of vehicles, several schemes have been proposed to solve this issue by precaching and relaying content via multiple relaying vehicles in the outage zone. However, because they involved the individual ranking of vehicles for precaching and allocated all of the available precaching amounts to the top-ranking vehicles, they decreased the success rate of content requests and the fairness of vehicle precaching. To overcome the problem of these previous schemes, this paper proposes a multiple precaching vehicle selection (MPVS) scheme that efficiently selects a content-precaching vehicle group with multiple precaching vehicles to precache relayed content in outage zones. To achieve this, we first designed numerical models to decide the necessity and the amount of precaching and to calculate the available precaching amounts of vehicles. Next, MPVS calculates all available vehicle sets and ranks each set based on the available precaching amount. Then, the content-precaching vehicle group is identified from the sets by considering both set rankings and vehicle communication overheads. MPVS also provides a content downloading process through the content-precaching vehicle group in the outage zone. Simulation results conducted in various environments with a content request model and a highway mobility model verified that MPVS was superior to a representative previous scheme.
在车联网中，车辆通过固定的路边单元从相应的内容服务器下载各种应用程序（包括安全、便利、娱乐和社交互动）所需的车辆信息。由于地理条件恶劣或部署成本高，可能难以充分部署足够的 RSU，因此车联网可能会在两个相邻的 RSU 之间出现未覆盖的中断区域。在这些中断区域内，车辆无法下载内容，因此车辆网络被定义为间歇性连接的车辆网络。在间歇性连接的车辆网络中，由于车辆用户请求的内容较大以及 RSU 之间的距离较长，回程链路的下载延迟和流量开销会增加。利用车辆的移动性信息，已经提出了几种方案，通过在中断区域中使用多个中继车辆进行预缓存和中继来解决此问题。然而，由于它们涉及到对车辆进行单独排名以进行预缓存并将所有可用的预缓存量分配给排名最高的车辆，因此降低了内容请求的成功率和车辆预缓存的公平性。为了解决这些先前方案的问题，本文提出了一种多预缓存车辆选择（MPVS）方案，该方案能够有效地选择具有多个预缓存车辆的内容预缓存车辆组，以在中断区域中预缓存中继内容。为此，我们首先设计了数值模型来决定预缓存的必要性和数量，并计算车辆的可用预缓存量。接下来，MPVS 根据可用预缓存量计算所有可用的车辆集，并对每个集进行排名。然后，通过考虑集排名和车辆通信开销，从集中识别内容预缓存车辆组。MPVS 还提供了在中断区域中通过内容预缓存车辆组进行的内容下载过程。在具有内容请求模型和高速公路移动性模型的各种环境中进行的仿真结果验证了 MPVS 优于代表性的先前方案。
