CR-SDVN: A Cognitive Routing Protocol for Software-Defined Vehicular Networks

Abstract

Due to the highly dynamic nature of cognitive vehicular networks, several sporadic links induce a long delay in the network. The selection of a stable route is therefore one of the key design factors to improve overall network stability, thereby reducing the end-to-end delay. Software-defined networking (SDN) is a novel approach that improves network intelligence. To this end, we propose a novel SDN-based routing protocol for cognitive vehicular networks that finds a stable route between source and destination. As this is a cognitive routing protocol, spectrum sensing is therefore the primary task of this algorithm to improve network stability by keeping primary user activity safe. We apply a belief propagation algorithm for channel selection. This is an SDN-based vehicular communications scheme where two nodes can only communicate when they have consensus about a common idle channel. The protocol has two phases: the registering phase and the route prediction phase. The SDN main controller (MC) is responsible for a global view of the network, whereas several local controllers (LCs) are responsible for localized global views of the network. This layering of controllers into two kinds (MC and LCs) improves the network performance in terms of end-to-end delay, high delivery ratio, and low overhead. We prove this in our simulation results by comparing our proposed scheme with two existing schemes (one with, and another without, SDN).