A bio-inspired leader election protocol for cognitive radio networks

The bio-inspired approach has been used effectively to address computing problems related to the domains, where nondeterminism is involved, e.g. sensing, assignment, localization, resource allocation, routing, optimization etc. The leader election in cognitive radio networks (CRN) is one such problem however no published work in the existing literature has used bio-inspired approach for leader election in CRN. The article proposes a bio-inspired ant colony approach for leader election in cognitive radio network (CRN). Our leader election algorithm is based on diffusion computation. We use metaheuristic method to explore CRN, create spanning tree, and find extrema that is declared leader. Our metaheuristic functions such as generation of ants, activity to search pheromone trail, pheromone evaporation (or daemon action) are composed of basic bio-inspired mechanisms, namely spreading, aggregation and evaporation. We validate our work with extensive simulation based on popularly used performance metrics. Further, the correctness proof of the protocol has also been included in the exposition. To the best of our knowledge, it is first bio-inspired extrema finding algorithm in cognitive radio networks.