Efficient Modeling of Interest Forwarding in Information Centric Vehicular Networks

Abstract

Vehicular networks (V-Nets) of the current era is widely used for information sharing and entertainment. Considering the popularity and demand for faster data communications, V-Nets are evolving towards an information-centric approach, namely the Information Centric Vehicular Networks (ICVN). In ICVN, nodes such as vehicles, roadside units, pedestrian devices, and sensors, generate interest packets and forward them to appropriate cache stores to retrieve desired data. Hence, an efficient interest forwarding algorithm in ICVN considerably enhances the content retrieval performance and make supports road safety, traffic management, environmental monitoring in real-vehicular environment. However, designing such efficient scheme is critical due to the involvement of various communication scenarios like vehicle-to-vehicle (V2V), vehicle-to-roadside unit (V2R), vehicle-to-in-vehicle sensors (V2S), vehicle-to-mobile infrastructure (V2I), and vehicle-to-personal device (V2P) and it demands a comprehensive and connected vehicular network. In this paper, we propose an interest forwarding scheme for ICVN with the above said realistic scenario. The interest forwarding process is governed by the Secretary Selection Problem (SSP) which guides a vehicular node to select the next level forwarder for locating the desired content. The goal is to select the best neighboring vehicle as the next forwarder thereby maximizing the chances of obtaining the requested data. The proposed scheme, named as Selection Based Interest Forwarding (SBIF) which uses Secretary Selection Problem (SSP) for governing the forward process to select the next level forwarder for locating the desired content. This scheme is analyzed mathematically and implemented in $ndn$ simulator. Performance is compared with existing state of the art schemes and observation shows that SBIF outperforms existing approaches considered for comparison.