## 2 Related Work
### Routing Schemes in CCN  
The author of [20] proposed updated content forwarding on the network to increase the cache hit ratio with minimum communication delay. According to the routing scheme proposed in [21], the most popular content has been cached in the network to satisfy the interest packets. It achieves a high packet delivery ratio. In their research paper [5], [PERSON] et al. used trajectory information sharing between highly mobile vehicles to ensure successful request satisfaction. The complete trajectory match for interest satisfaction leads the content provider vehicle away from the consumer vehicle. It increases the communication delay in the network.  
In [22], the Markov decision model is used to predict the movement direction of vehicles to cache the most popular content on RSU and vehicles to achieve a high packet delivery ratio. In [10], the content-centric network properties are utilized in smart vehicles. It ensures a successful packet delivery rate by sharing the route information to neighbor vehicles. The vehicles with the same direction respond to each other. It ensures successful communication within the minimum delay.The scheme proposed in [23] tracks the movement of the vehicle on the specific lanes and ensures successful communication. The resource allocation problem is modeled as a Markov decision model process and using approximation function in [24]. The authors proposed a resource-allocation method based on an actor-critic (A3C) learning algorithm to achieve successful communication within high dimensions and have better convergence properties [24]. CCN is proposed for the collection of vehicular traffic information [25]. A unique name is assigned to traffic events, and location-based routing is adopted. For the efficient collection of information cache hit and cache miss is studied. The proposed caching is based on the vehicle movement and probability of the channel usage ratio. Caching and forwarding of content in NDN induces the redundancy of the content due to multiple copies of the same content, which leads to increase overhead in the network. In [26], optimal caching policy is studied based on the popularity of the content considering constraints such as available storage and bandwidth.  
A probabilistic interest forwarding mechanism is presented in [27]. It considers the probability of forwarding the interest to be high in a low dense vehicular environment and vice versa. The [PERSON] et al. [28] proposed a push-based data forwarding scheme. The relay vehicles receive the segmented data packets.  
According to previous research findings, V2V provides efficient communication and various traffic-aware messages broadcasting to neighbor vehicles. It increases network load and compromises the delay. In V2I, vehicles request data from RSU to satisfy the requests. However, data authentication and privacy policy are not defined. Vehicles have a built-in cache to save data and satisfy requests. However, they did do provide the validity of data in the cache and RSU.  
There are several research contributions that solve the problem of frequent communication link disruption between vehicles and decrease broadcasting storms in the network. In cluster-based vehicular routing protocols, head vehicles satisfy the interests of the network. However, if the head vehicle is not available in the network, it creates an interest broadcasting storm. This increases network load and packet collision probability, and re-polling for head vehicle selection increases the communication delay.