NOA: A Scalable Multi-Parent Clustering Hierarchy for WSNs
Author(s) -
Melanie CreeGreen,
J.G. Delgado-Frias,
Mike Hughes,
Brion J. Burghard,
K.L. Silvers
Publication year - 2012
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2012.06.163
Subject(s) - computer science , scalability , cluster analysis , hierarchy , hierarchical clustering , overhead (engineering) , distributed computing , wireless sensor network , hierarchical network model , network topology , computer network , machine learning , database , economics , market economy , operating system
NOA is a multi-hop, multi-parent, N-tiered, hierarchical clustering algorithm that provides a scalable, robust and reliable solution for autonomous configuration of large-scale wireless sensor networks. The novel clustering hierarchy's inherent benefits can be utilized by in-network data processing techniques to provide a robust data processing solution capable of reducing the amount of data sent to data sinks. Utilizing a multi-parent framework, NOA reduces the cost of network configuration when compared to current hierarchical beaconing solutions by removing the r-hop fi (where r is the radius of the cluster). NOA instead utilizes common children to distribute information about the hierarchy's topology to siblings. NOA2, a two-parent clustering hierarchy solution, and NOA3, the three-parent variant, saw up to an 83% and 72% reduction in communication overhead, respectively, when compared to configuring the network using a one-parent hierarchical beaconing solution, as well as 92% and 88% less overhead when compared to two-and three-parent variants of hierarchical beaconing
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