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http://dx.doi.org/10.3745/KIPSTA.2010.17A.2.103

A Design of Efficient Cluster Sensor Network Using Approximate Steiner Minimum Tree  

Kim, In-Bum (김포대학 IT학부)
Publication Information
The KIPS Transactions:PartA / v.17A, no.2, 2010 , pp. 103-112 More about this Journal
Abstract
Cluster sensor network is a sensor network where input nodes crowd densely around some nuclei. Steiner minimum tree is a tree connecting all input nodes with introducing some additional nodes called Steiner points. This paper proposes a mechanism for efficient construction of a cluster sensor network connecting all sensor nodes and base stations using connections between nodes in each belonged cluster and between every cluster, and using repetitive constructions of approximate Steiner minimum trees. In experiments, while taking 1170.5% percentages more time to build cluster sensor network than the method of Euclidian minimum spanning tree, the proposed mechanism whose time complexity is O($N^2$) could spend only 20.3 percentages more time for building 0.1% added length network in comparison with the method of Euclidian minimum spanning tree. The mechanism could curtail the built trees' average length by maximum 3.7 percentages and by average 1.9 percentages, compared with the average length of trees built by Euclidian minimum spanning tree method.
Keywords
Cluster Sensor Network; Approximate Steiner Minimum Tree; Euclidean Minimum Spanning Tree; Steiner point; Steiner Graph;
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Times Cited By KSCI : 5  (Citation Analysis)
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