Congestion Control in Wireless Sensor Networks Based on the Bird Flocking Behavior

Authors:
Pavlos Antoniou;Andreas Pitsillides;Andries Engelbrecht;Tim Blackwell;Loizos Michael
Affiliations:
Department of Computer Science, University of Cyprus, Cyprus;Department of Computer Science, University of Cyprus, Cyprus;Department of Computer Science, University of Pretoria, South Africa;Department of Computing, Goldsmiths College, University of London, UK;Department of Computer Science, University of Cyprus, Cyprus
Venue:
IWSOS '09 Proceedings of the 4th IFIP TC 6 International Workshop on Self-Organizing Systems
Year:
2009

Citing 3
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Abstract

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.