Optimized interest forwarding in information centric vehicular networks using general secretary problem

Abstract Vehicular networks of current era is not limited only to road safety and traffic management. It is been widely accepted as a network for information sharing, social networking and entertainment. With the advent of smart vehicles, the demand of vehicular network centric applications are getting popular. In one way, these applications demand faster data access and on the other hand, the underlying challenges of vehicular networks such as intermittent connectivity, low bandwidth and unpredictable vehicle movements impose considerable hindrance on communications. That is why, the vehicular communication is moving towards information centric approach so that the benefits of Information Centric Network (ICN) can be utilized. However, inherent challenges of vehicular communication and the lack of adequate protocols to implement content centric approach makes the extension of ICN into vehicular communications difficult. In ICN, a node generates interest packets to find a content. The interest is forwarded to an appropriate cache store to get the data. Hence, efficient forwarding of interest packets can considerably improve the content retrieval delay and can reduce network load. The interest forwarding techniques designed for wired ICN are not suitable for vehicular network due to computational complexity and bandwidth crisis. Hence, Information Centric Vehicular Network (ICVN) demands a new design for interest forwarding. Influenced by the need of the current time in vehicular communication, this research is aimed at developing an efficient interest forwarding mechanism for ICVN. The proposed algorithm models the interest forwarding task as a general secretary problem and finds the best node (or set of nodes) in the network to forward the interest packet. The protocol performance is examined in a simulation testbed designed in ndnSim-2.0 and compared with existing forwarding approaches. Observation demonstrates a better performance of the said vehicle with respect to content retrieval latency and network overhead.