In vehicular networks, some edge servers may not function properly due to the time-varying load condition and the uneven computing resource distribution, resulting in a low quality of caching services. To overcome this challenge, we develop a Vehicular dew computing (VDC) architecture for the first time by combining dew computing with vehicular networks, which can achieve wireless communication between vehicles in a resource-constrained environment. Consequently, it is crucial to develop an adaptive caching scheme that empowers vehicles to form efficient cooperation in VDC. In this paper, we propose an intelligent caching scheme based on VDC architecture, which includes two parts. First, to meet the dynamic nature of VDC, a spatiotemporal vehicle clustering algorithm is proposed to establish adaptive cooperation to assist content caching for vehicles. Second, the multi-armed bandit algorithm is employed to select suitable content for caching in vehicles based on real-time file popularity, and a model is established to dynamically update each vehicle’s request preferences. Extensive experiments are conducted to demonstrate that the proposed scheme has excellent performance in terms of cluster head stability and cache hit rate.

在车载网络中，由于负载情况时变、计算资源分布不均匀，一些边缘服务器可能无法正常工作，导致缓存服务质量低下。为了克服这一挑战，我们首次开发了车载露水计算（VDC）架构，将露水计算与车载网络相结合，可以在资源受限的环境下实现车辆之间的无线通信。因此，开发一种自适应缓存方案使车辆能够在 VDC 中形成有效的合作至关重要。在本文中，我们提出了一种基于VDC架构的智能缓存方案，该方案包括两部分。首先，为了满足VDC的动态特性，提出了一种时空车辆聚类算法来建立自适应协作来辅助车辆的内容缓存。其次，采用多臂老虎机算法根据实时文件流行度选择合适的内容缓存在车辆中，并建立模型来动态更新每个车辆的请求偏好。大量的实验表明，该方案在簇头稳定性和缓存命中率方面具有优异的性能。