A new routing metric and protocol for multipath routing in cognitive networks

Routing in cognitive networks is a challenging problem due to the primary users´ (PU) activities and mobility. Multipath routing is a general solution to improve reliability of connections. Existing multipath routing metrics for traditional wireless networks do not take into account PUs´ activities. This work introduces a new routes selection metric for multipath routing in cognitive networks. Routes closeness, the proposed metric, favors routes that are not close to each other. Selecting non-close routes makes them less vulnerable to PUs´ activities as it would be less possible for an active mobile PU to interrupt all the routes at the same time. We describe our new routes closeness metric along with a routing protocol that make use of it to enhance the performance in cognitive networks. Simulation results show the effectiveness of the new metric in increasing connection reliability and end-to-end throughput to up to 48% compared to other algorithms, especially with increasing PUs´ mobility and secondary user´s (SUs) density.