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

Abstract

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.