Routing In Cognitive Networks Research Articles

Spectrum and Delay Efficient Routing Protocol for Mobile Cognitive Ad-Hoc Networks

The ad hoc mobile cognitive network is an advanced network technology for the Federal Communications Commission (FCC) problem of frequency deficiency. Cognitive radio networks are cognitive networks that select their network parameters based on the network environment. In a cognitive radio network, two users, the primary and the secondary or the cognitive user, gain access to the spectrum available to communicate with each other when the primary user accesses the spectrum. The secondary user should leave the spectrum and use the spectrum for the spectrum if the spectral hole is available for transmission. Therefore, routing in cognitive networks is a challenge and a challenge in mobile cognitive networks because of node mobility, the primary user interface, and the lack of spectrum. A delay minimized routing protocol is proposed for minimum delay route selection between the source and destination, which is improved version of AODV. The numerical and ns2 simulation results for the proposed protocol significantly state that delay minimized routing protocol (DMR) is better in terms of average end-to-end delay and average throughput.

Spectrum aware on-demand routing in cognitive radio networks

Spectrum aware on-demand routing in cognitive radio networks

Collaborative Multi-hop Routing in Cognitive Wireless Networks

The collaboration of nodes in cognitive wireless networks is a large challenge. This paper studies the collaborative multi-hop routing in cognitive networks. We propose a new algorithm to construct the collaborative routing in multi-hop cognitive networks. Our algorithm takes into account the interference among nodes including primary and secondary users. The clustering and collaboration are exploited to improve the performance of collaborative routing in multi-hop cognitive wireless networks with multiple primary and secondary users. By analyzing the maximum transmission distance, collaborations, transmission angle control and power control, and channel allocation, we propose a new clustering-based collaborative multi-hop cognitive routing algorithm to attain better network performance. Simulation results show that our approach is feasible and effective.

Cognitive cross-layer multipath probabilistic routing for cognitive networks

Mobile Ad-hoc NETworks (MANETs) is a set of mobile nodes that can move around arbitrarily, and communicate with others in a multi-hop fashion without any assistance of base stations. With recent advances in Cognitive Radio (CR) technology, it is possible to apply the Dynamic Spectrum Access model in MANETs. This introduces the concept of Cognitive Radio Ad Hoc Networks (CRAHNs). Applying CR techniques provides better throughput, even in congested spectrum along with better propagation characteristics. CRAHN is a kind of intelligent network that is aware of its surrounding environment, and adapts to the transmission or reception parameters to achieve efficient communication without interfering with primary users. Routing in CR environment is a challenging task as the availability of channel is constrained by the presence of primary user. The problem of routing in CRAHNs targets the creation and maintenance of wireless multi-hop paths among cognitive nodes by deciding both the spectrum to be used and the relay nodes of the path. This paper proposes a cognitive cross-layer multipath probabilistic routing for cognitive radio based networks. The proposed solution uses spectrum holes identified by MAC layer, decides the channel to be used and transmit power level for each hop in the path. The proposed solution is implemented in NS2, and performance of the proposed solution is compared with the existing solution from the literature. The paper also shows that the proposed solution outperforms existing solution in terms of packet delivery ratio, average end-to-end delay and energy consumed per data packet.

Learning-Based Routing in Cognitive Networks

Intelligent Routing can influence the overall performance of a communication network’s throughput and efficiency. Routing strategies is required to adapt to changing network loads and different topologies. Learning from the network environment, in order to optimally adapt the network settings, is an essential requirement for providing efficient communication services in such environments. Cognitive networks are capable of learning and reasoning. They can energetically adapt to varying network conditions in order to optimize end-to-end performance and utilize network resources. In this paper we will focus machine learning in routing scheme that includes routing awareness, a routing reconfiguration.

Channel assignment with closeness 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. Routes closeness metric was proposed for multipath routing in cognitive networks; however, the proposed technique supports only one channel [4]. This work proposes a multichannel assignment technique for multipath routing using routes closeness as the routing metric. It relies on the nodes of the different paths to early detect the existence of PUs and notify nodes on other routes to avoid using the PU’s channel that is going to be interrupted. In case the field has PUs occupying all channels, channels assigned to nodes based on how far the nodes are from the PU. Simulation results show the effectiveness of the channel assignment technique in increasing end-to-end throughput and decreasing delay.

Reactive routing for mobile cognitive radio ad hoc networks

Although more than a decade has passed from the proposal of the Cognitive Radio paradigm, in these years the research has mainly focused on physical and medium access issues, and few recent works focused on the problem of routing in cognitive networks. This paper addresses such a problem by evaluating the feasibility of reactive routing for mobile cognitive radio ad hoc networks. More specifically, we design a reactive routing protocol for the considered scenario able to achieve three goals: (i) to avoid interferences to primary users during both route formation and data forwarding; (ii) to perform a joint path and channel selection at each forwarder; (iii) to take advantage of the availability of multiple channels to improve the overall performance. Two different versions of the same protocol, referred to as Cognitive Ad-hoc On-demand Distance Vector (CAODV), are presented. The first version exploits inter-route spectrum diversity, while the second one exploits intra-route spectrum diversity. An exhaustive performance analysis of both the versions of the proposed protocol in different environments and network conditions has been carried out via numerical simulations. The results state the suitability of the proposed protocol for small mobile cognitive radio ad hoc networks.

Routing for cognitive radio networks consisting of opportunistic links

Cognitive radio (CR) has been considered a key technology to enhance overall spectrum utilization by opportunistic transmissions in CR transmitterreceiver link(s). However, CRs must form a cognitiv...