Gymkhana: A Connectivity-Based Routing Scheme for Cognitive Radio Ad Hoc Networks

The topology of a cognitive radio Ad Hoc network is highly influenced by the behavior of both licensed (primary) and unlicensed (secondary) users. In fact, the network connectivity could be impaired by the activity of primary users. This aspect has a significant impact on the design of routing protocols. We design a routing scheme for cognitive radio Ad Hoc networks, named Gymkhana, which is aware of the degree of connectivity of possible paths towards the destination. Gymkhana routes the information across paths that avoid network zones that do not guarantee stable and high connectivity. To this aim we use a mathematical framework, based on the Laplacian spectrum of graphs, that allows a comprehensive evaluation of the different routing paths of the cognitive radio network. Laplacian matrixes are used to compute the connectivity of the different network paths. Gymkhana uses a distributed protocol to collect some key parameters related to candidate paths from an origin to a destination. The parameters are fed into a basic mathematical structure which is used to compute efficient routing paths. Besides the basic idea of Gymkhana, the use of Laplacian matrixes to derive a closed formula to measure the path connectivity is another contribution of ours.