Congestion control in wireless sensor networks based on the bird flocking behavior

Recently, performance controlled wireless sensor networks have attracted significant interest with the emergence of mission-critical applications (e.g. health monitoring). Performance control can be carried out by robust congestion control approaches that aim to keep the network operational under varying network conditions. In this study, swarm intelligence is successfully employed to combat congestion by mimicking the collective behavior of bird flocks, having the emerging global behavior of minimum congestion and routing of information flow to the sink, achieved collectively without explicitly programming them into individual nodes. This approach is simple to implement at the individual node, while its emergent collective behavior contributes to the common objectives. Performance evaluations reveal the energy efficiency of the proposed flock-based congestion control (Flock-CC) approach. Also, recent studies showed that Flock-CC is robust and self-adaptable, involving minimal information exchange and computational burden.