# A Smart Approach to Electric Vehicle Optimization via IoT-Enabled Recommender Systems
## 3 Infra-Structure Analysis
### Routing  
Using distance vector information, the proposed upgraded DVMRP (Distance Vector Multicast Routing Protocol) distributes data about participating EVs across the network, including their location, vehicle ID, distance and charge state. Comparably, the embedded sensor nodes of the participating EVs use this information to communicate with other EVs via hop count and BS, sharing the data they have collected during the network. Additionally, an administrator helps to monitor the web from a distance [34]. The proposed DVMRP (Distance Vector Multicast Routing Protocol) consists of a variety of components, including routing protocols, sensor nodes, prediction algorithms, and converters. This routing concept creates a network topological infrastructure in which all EVs share information. It allows drivers to process routing and pricing requests across the network. However, the existing routing mechanism transfers data from the source to the destination depending on hop count. While this technique allows for roaming depending on hop count selection, it does not provide effective communication inside the network infrastructure. In the traditional routing approach, communication of data from source to destination will depend on hop-count information. Although this permits roaming, it frequently fails to ensure efficient communication within the network infrastructure [37]. The modernized DVMRP for EVs aims to fix these issues by: (1) Using advanced routing techniques to optimize data routes; (2) Improving data prediction and processing techniques to better anticipate and control network traffic; and (3) To ensure safety and reliability, robust protection and charge control methods have been implemented. These enhancements are designed to achieve better network lifetime, minimizing delays in data transmission and enhancing overall performance and resource utilization. To improve routing, the Distance Vector Multicast Routing Protocol (DVMRP) is used. Initially, DVMRP is set to zero, indicating that no pathways are created. The vehicle sequence is then reset to zero to prepare for the processing of electric vehicles (EV). The next step is to loop through each EV in the network, where \(n\) is the total number of EVs. Each EV, designated by a unique ID, is parked at a charging station M. For each EV, the protocol repeats the same steps. If an EV is not present, the DVMRP remains zero, indicating that there is no available path. If the EV is not at the charging station, it moves on to the next state in the sequence, and its count increases by one. Subsequently, communication is established with nearby charging stations to explore multiple routing paths. When the EV sequence is incremented by one, the sequence is updated based on the EV's current state. Since the remote administrator is crucial to maintaining the network's dependability metrics, the administrator is essential in our suggested approach. Below is a more detailed explanation of how the enhanced DVMRP routing protocol is implemented in the proposed model--it first connects to adjacent EVs to update the routing table [35]. Here, EVs that are a member of the network link with other EVs through base stations (BSs) and communicate with close peers based on the hop count. Also, our improved DVMRP protocol will allow participating EVs to update their routing data when their positions change, while maintaining the same level of consistency in the parameters, like the proximity hop count data. Therefore, the EV guarantees continuous connectivity throughout the communication process, even when it roams to a different base station. It does this by maintaining accurate and constant communication within the network. The algorithm in the paper, Algorithm 1,comprehensively explains forwarding and storing data related to route replies (RREP) and route requests (RREQ) within the network.