Management of cognitive radio ad hoc networks using a congestion-based metric

In this paper, we propose a new network management protocol to address the unique challenges of managing cognitive radio ad hoc networks that have distributed, multihop architectures with dynamic spectrum availability. We focus on performance management for these networks, and address the problem of network congestion for secondary users, because of its significant impact on data throughput. Specifically, we define a performance metric, the average congestion level of the network, and derive it analytically as a function of the primary users’ activities and the secondary users’ strategy. For practical implementation, we further propose a cluster-based management architecture that utilizes a designated central manager and cluster heads that function as distributed managers. The cluster heads collect information from multiple layers of the protocol stack using new MIB (management information base) variables to capture the characteristics of cognitive radio ad hoc networks, such as the location-dependent spectrum availability. The objective of the management action is to utilize a networklevel view of the congestion situation in the network by directing the secondary users to select the highestquality links available and avoid congested clusters. This hierarchical networkmanagement design allows us to take advantage of its scalability to achieve near-real-time management. Numerical results demonstrate the effectiveness of the proposed scheme. Copyright © 2013 John Wiley & Sons, Ltd.