Cognitive greedy-backhaul routing metric exploiting cross-layer design for wireless ad hoc and mesh networks

Abstract

We propose a ‘cognitive greedy-backhaul’ (CGB) routing metric that associates routing with an appropriate channel assignment scheme to determine cognitive backhaul links. Those backhaul links are established in congested areas where higher capacities are required. CGB forces nodes to select those backhaul links which have higher capacities to reduce the relaying burdens that are caused by nodes hopping around in the network. CGB performance is compared with shortest-path (SH) and available capacity-aware routing (AC) metrics and simulation results show that the CGB routing metric can significantly improve end-to-end throughput by using those cognitive backhaul links.