Joint Deterministic and Probabilistic Edge Caching Minimized Service Time for Cooperative Video Transmission in VANETs

Video streaming in vehicular ad-hoc networks (VANETs) faces significant challenges due to the dynamic nature of vehicles, frequent disconnections, and huge demands for high data rate communications. These challenges make it longer for vehicle users (VUs) to complete their sessions in video applications and services (VASs). In this paper, we fully utilize the benefits of both deterministic and probabilistic edge caching (DPC) techniques for cooperative transmission to minimize the service time in VASs. To do so, a DPC optimization problem is formulated and solved for the optimal results of 1) caching placement in roadside units (RUs) and 2) caching probability in VUs under the constraint on caching storage resource. Genetic algorithms are modified to deal with the complexity of two types of optimization variables, i.e., integer variable for deterministic caching and real variable for probabilistic caching, and thus ensuring high stability and accuracy. Simulation results demonstrate that the DPC method outperforms the other conventional schemes in terms of service time while efficiently utilizing the storage of RUs and VUs. Important findings are also analyzed and discussed to provide more useful insights into the design of edge caching techniques for VASs in VANETs.