Multimodal Named Data Discovery with Interest Broadcast Suppression for Vehicular CPS

Abstract

Cyber-physical system (CPS) provides a well-organized integration between communication, computation, and control (3C) technologies. CPS has been widely used in the vehicular networks and it requires to discover multimodal data from the physical system to take appropriate decision and actions, for example, congestion warnings, applying brakes, adjusting speed limits, etc. Information discovery and availability at individual network elements is one of the fundamental foundations of CPS. In this paper, we proposed two multimodal network information discovery schemes for vehicular CPS using the Named Data Networking (NDN). One of the proposed schemes simply modifies the pull-based NDN communication mechanism to discover multimodal multi-hop data from the network and the other scheme uses the Interest broadcast suppression (IBS) mechanism. Interest broadcast suppression scheme adapts the holding time technique to defer the Interest forwarding and its computation involves the hop-count, distance, and other network parameters. Simulation results show that the proposed schemes discover about 172% and 162% more multimodal information from approximately 283% and 210% more network area by suppressing approximately 50% of the Interest broadcast storm in highway and the urban traffic scenarios, respectively.