## 2 Related Work  
Data acquisition models are usually discussed together with the routing protocols in vehicular networks. In recent years, node cooperation is utilized in data acquisition for vehicular networks. In [12], several autonomous mobile nodes compose a content replication group. Each node replicates a subset of all the contents from the server respectively and shares them with other nodes in its group at a small cost. Thus, the overall access ratio is improved. In [13], based on peer-to-peer (P2P) communication principles, [PERSON] and [PERSON] construct an optimized framework to manage content replication and dissemination through a mobile vehicular network. Their solution overcomes the bandwidth restriction problem in inter-vehicle content distribution and regards a vehicular flow as a virtual backbone in the scenarios without fixed infrastructures. In [14], [PERSON] et al. focus on a static content replication under the random walk mobility model. They construct an optimal formula with constraints to find a good distribution schema, and analyse the influences of relevant network parameters, such as the total system storage, the data item size and the vehicle trip duration. For the online video applications, [PERSON] and [PERSON], in [15], propose a probabilistic trust-aware data replication strategy. It uses a data replication tree to represent the transmission process of a content from its source to its destination, and defines a replica cost function and a trust calculation metric for replica location and data replication with read and update operations. The data acquisition models mostly use mobile vehicular nodes to carry contents. Specifically, according to the requests and the mobility features of vehicles, the number of content replicas and their appropriate carriers are calculated. Thereafter, these carriers respond to the requests via V2V communications when encountering those request senders during their travel time. Considering the deficiency of existing data replication schemes which take a complete content as the replication unit, [PERSON] et al. do research on packet-level data replication in [16]. They explore the contact-duration-aware data replication problem in theory and give a centralized solution to better utilize the limited storage and communication chances. In addition, a distributed replication algorithm is designed with a low computing complexity. Experiments based on synthetic and realistic trajectories confirm the close-to-optimal performance of this proposal. Regarding the content replicas as open resources, [PERSON] et al. put forward a data distribution scheme using local measurements only, which well approximates an optimal solution and remains robust against network and demand dynamics [17]. Nevertheless, this scheme applies to mobile networks with low velocity, since it is based on multi-hop data transfers among mobile nodes. In [18], [PERSON] et al. model the relationships among the number of replicas of a packet, the replication limit and the queue length of vehicular nodes. Then, a distributed capacity-constrained replication scheme is proposed to dictate how each vehicle adaptively determines its replication strategy subject to the current network capacity. Experiments based on real vehicle GPS traces show a high access ratio. In [19; 20], two origin-destination-based content replication schemes, i.e., ODCRep and GO-DCR, select appropriate nodes to replicate contents based on the vehicles' origin and destination points. Specifically, ODCRep controls the number of replicas in the scenario via efficient algorithms, and hence achieves high coverage and saves resources, while GO-DCR, as a geo-localized solution, increases content availability and reduces delivery cost. Regarding the significance of roadside infrastructure on the data delivery in cooperative vehicle-infrastructure systems, some studies analyze the features of V2U communications and optimize the deployment of roadside units [21; 22; 23]. [PERSON] et al.