Named data networking (NDN) is a newly proposed paradigm for future Internet, in which communication among nodes is based on data names, decoupling from their locations. In dynamic and self-organized cognitive radio ad hoc networks (CRAHNs), it is difficult to maintain end-to-end connectivity between ad hoc nodes especially in the presence of licensed users and intermittent wireless channels. Moreover, IP-based CRAHNs have several issues like scalability, inefficient-mapping, poor resource utilization, and location dependence. By leveraging the advantages of NDN, in this paper, we propose a new cross layer fine-grained architecture called named data networking for cognitive radio ad hoc networks (NDN-CRAHNs). The proposed architecture provides distinct features such as in-networking caching, security, scalability, and multipath routing. The performances of the proposed scheme are evaluated comparing to IP-based scheme in terms of average end-to-end delay and packet delivery ratio. Simulation results show that the proposed scheme is effective in terms of average contents download time and packet delivery ratios comparing to conventional cognitive radio ad hoc networks.
End-to-End Delay Analysis in Cognitive Radio Ad Hoc Networks with Different Traffic Models
