A dominance-based stepwise approach for sensor placement optimization

[Display omitted] •We show that the stepwise approach is better suited for sensor placement.•We use terrain information and intersensor relationship information to facilitate the optimization.•We investigate the effect of terrain irregularity on optimization algorithm performances.•The proposed meth...

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Bibliographic Details
Published in:Applied soft computing 2015-03, Vol.28, p.466-482
Main Authors: Ko, Albert Hung-Ren, Jousselme, Anne-Laure, Sabourin, Robert, Gagnon, Francois
Format: Article
Language:English
Subjects:
Coverage
Evolutionary Algorithm
Genetic Algorithm
Optimization
Sensor placement
Simulated Annealing
Wireless communications
Wireless Sensor Networks
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Summary:[Display omitted] •We show that the stepwise approach is better suited for sensor placement.•We use terrain information and intersensor relationship information to facilitate the optimization.•We investigate the effect of terrain irregularity on optimization algorithm performances.•The proposed methods show that information on terrain elevation can be extracted as the dominance factor. A Wireless Sensor Network (WSN) usually consists of numerous wireless devices deployed in a region of interest, each of which is capable of collecting and processing environmental information and communicating with neighboring devices. The problem of sensor placement becomes non trivial when we consider environmental factors such as terrain elevations. In this paper, we differentiate a stepwise optimization approach from a generic optimization approach, and show that the former is better suited for sensor placement optimization. Following a stepwise optimization approach, we propose a Crowd-Out Dominance Search (CODS), which makes use of terrain information and intersensor relationship information to facilitate the optimization. Finally, we investigate the effect of terrain irregularity on optimization algorithm performances, and show that the proposed method demonstrates better resistance to terrain complexity than other optimization methods.
ISSN:1568-4946
1872-9681
DOI:10.1016/j.asoc.2014.11.051