Title
Congestion Control in Wireless Sensor Networks Based on the Bird Flocking Behavior
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.
Year
DOI
Venue
2009
10.1007/978-3-642-10865-5_21
IWSOS
Keywords
Field
DocType
proposed flock-based congestion control,congestion control,collective behavior,information flow,robust congestion control approach,individual node,bird flocking behavior,emergent collective behavior,minimum congestion,global behavior,performance control,performance evaluation,wireless sensor networks,swarm intelligence,wireless sensor network,information exchange,energy efficient
Key distribution in wireless sensor networks,Collective behavior,Efficient energy use,Computer science,Swarm intelligence,Information exchange,Flocking (behavior),Computer network,Network congestion,Wireless sensor network,Distributed computing
Conference
Volume
ISSN
Citations 
5918
0302-9743
4
PageRank 
References 
Authors
0.41
5
5
Name
Order
Citations
PageRank
Pavlos Antoniou135317.04
Andreas Pitsillides299895.02
Andries Engelbrecht3694.36
Tim Blackwell434727.87
Loizos Michael517422.10