Improving Quality of Service Provisioning of Optimised Cuckoo Search Ad Hoc on-demand Distance Vector Routing Scheme for Cognitive Radio Ad Hoc Networks.

Spectrum mobility, cloud computing and the Internet of Things (IoTs) create large data sets, while the demand for more spectrum is increasing. Unfortunately, the spectrum is a scarce resource which is being underutilized by licensed users. The cognitive radio network, also known as intelligent radio, is a network that can adjust to environment changes and, detect available channels. It has emerged as a promising solution for the underutilization of the licensed spectrum and overcrowded free spectrum. Furthermore, given spectrum mobility, frequent link breakages impact negatively on the delivery of packets and the performance of the network. Hence there is need to address the routing problem. We therefore investigated which control methods can be utilized to improve the QoS provisioning in CRAHNs to minimize the signal overhead and to increase the achievable throughput.The study integrated the QoS requirements with optimized cuckoo search (OCS) algorithm to enhance the ad hoc on-demand distance vector (AODV) algorithm to establish a scheme we refer to as OCS-AODV. NS 2 simulation were run on Linux operating system. The comparative results show that the proposed scheme performed well in terms of end-to-end delay and throughput. However, the scheme does not backup alternative paths which can be used in the event of link breakages. The route discovery has to be re-initiated again. Though the route discovery process is faster because of the capability of the CS technique, it still degrades the performance of the scheme.