Title :
A clustering method for wireless sensors networks
Author :
Fouchal, S. ; Monnet, Q. ; Mansouri, D. ; Mokdad, L. ; Ioualalen, M.
Author_Institution :
Lab. LSIIT (BFO), Univ. of Strasbourg, Strasbourg, France
Abstract :
Clustering algorithms have been widely used in many domains so as to partition a set of elements into several subsets, each subset (or “cluster”) grouping elements which share some similarities. These algorithms are particularly useful in wireless sensor networks (WSNs), where they allow data aggregation and energy cuts. By forming clusters and electing cluster heads responsible for forwarding their packets, the small devices that compose WSNs have not to reach directly the base station (BS) of the network. They spare energy and they can lead further in time their measuring task, so as to detect forest fires or water pollution for example. In this paper, we will apply a new and general clustering algorithm, based on classificability and ultrametric properties, to a WSN. Our goal is to get clusters with a low computational complexity, but with an optimal structure regarding energy consumption.
Keywords :
computational complexity; pattern clustering; wireless sensor networks; WSN; base station; cluster heads; clustering method; computational complexity; data aggregation; energy consumption; energy cuts; forest fire detection; general clustering algorithm; subset grouping elements; ultrametric property; water pollution; wireless sensors networks; Ad hoc networks; Clustering algorithms; Energy consumption; Energy measurement; Partitioning algorithms; Sensors; Wireless sensor networks;
Conference_Titel :
Computers and Communications (ISCC), 2012 IEEE Symposium on
Conference_Location :
Cappadocia
Print_ISBN :
978-1-4673-2712-1
Electronic_ISBN :
1530-1346
DOI :
10.1109/ISCC.2012.6249414