Graph Based Cooperative Forwarding in Information Centric Vehicular Networks

The rise of data intensive applications reveal the limitations of IP-based networking, particularly in dynamic vehicular environment. Transitioning to Information Centric Network (ICN) addresses these limitations by focusing on content retrieval from any suitable location rather than completely relying on content server or host-to-host communication. The content based communication uses an interest packet to seek named data. The interest packets are forwarded through the network to locate and retrieve content. In general the ICN uses Forwarding Information Base (FIB) tables for efficient forwarding of interest. However, in wireless environment like Vehicular Network (V-Net), use of FIB is expensive due to high bandwidth demand for maintenance. Hence, interest forwarding approach without FIB is much popular. In this paper, an interest forwarding technique for Information Centric Vehicular Networks (ICVNs) is proposed without the use of FIB. The prime objective of the algorithm is to reduce content retrieval time and optimize network overhead and throughput. For that purpose the network is modeled as a graph and partitioned into groups where each group is managed by a group leader. The group members cooperate with leader and share local information. The leaders, on the other hand cooperate with other group leaders and share information in the global level. Interest packets are forwarded by leaders on behalf of a group there by accelerating the content retrieval process. The proposed algorithm is named as GCF (Graph based Cooperative Forwarding) and is simulated in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ndnSim</i>-2.0. The performance of GCF is compared with the other two contemporary protocols, and observation shows better performance of the new approach, specifically in a densely populated scenario, compared to other benchmark algorithms. Various parameters used in the comparison are end-to-end latency, interest loss rate, network overhead, throughput, and server hit ratio. Quantitatively, the proposed protocol shows nearly 10% improvement in latency, 40% improvement in interest packet loss, and 60% improvement in network overhead.