Mimicking the bird flocking behavior for controlling congestion in sensor networks

This study deals with the problem of congestion in wireless sensor networks (WSNs) and proposes a robust and self-adaptable nature-inspired congestion control approach for realtime event-based applications. WSNs face important limitations in terms of energy, memory and computational power. The uncontrolled use of limited resources in conjunction with the unpredictable nature of WSNs in terms of traffic load injection, wireless channel capacity fluctuations and topology modifications (e.g. due to node failures) may lead to congestion. Inspiration is drawn from the flocking and obstacle avoidance behavior of birds to `guide' packets bypass obstacles like congestion regions and dead node zones. Recent studies showed that the flock-based congestion control (Flock-CC) approach is robust, self-adaptable and energy-efficient, involving minimal information exchange and computational burden when used in uniform grid topologies. The applicability of the Flock-CC in random topologies is investigated in this paper. Performance evaluations showed that Flock-CC was able to both alleviate congestion and minimize energy tax. Also, Flock-CC demonstrated robustness against failing nodes, and outperformed other congestion-aware routing approaches in terms of packet delivery ratio, end-to-end delay and energy tax.