Optimal Sensor Deployment for Wireless Surveillance Sensor Networks by a Hybrid Steady-State Genetic Algorithm

Jae-Hyun SEO  Yong-Hyuk KIM  Hwang-Bin RYOU  Si-Ho CHA  Minho JO  

Publication
IEICE TRANSACTIONS on Communications   Vol.E91-B   No.11   pp.3534-3543
Publication Date: 2008/11/01
Online ISSN: 1745-1345
DOI: 10.1093/ietcom/e91-b.11.3534
Print ISSN: 0916-8516
Type of Manuscript: Special Section PAPER (Special Section on Emerging Technologies for Practical Ubiquitous and Sensor Networks)
Category: 
Keyword: 
wireless sensor networks,  surveillance sensor deployment,  hybrid steady-state genetic algorithm,  

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Summary: 
An important objective of surveillance sensor networks is to effectively monitor the environment, and detect, localize, and classify targets of interest. The optimal sensor placement enables us to minimize manpower and time, to acquire accurate information on target situation and movement, and to rapidly change tactics in the dynamic field. Most of previous researches regarding the sensor deployment have been conducted without considering practical input factors. Thus in this paper, we apply more real-world input factors such as sensor capabilities, terrain features, target identification, and direction of target movements to the sensor placement problem. We propose a novel and efficient hybrid steady-state genetic algorithm giving low computational overhead as well as optimal sensor placement for enhancing surveillance capability to monitor and locate target vehicles. The proposed algorithm introduces new two-dimensional geographic crossover and mutation. By using a new simulator adopting the proposed genetic algorithm developed in this paper, we demonstrate successful applications to the wireless real-world surveillance sensor placement problem giving very high detection and classification rates, 97.5% and 87.4%, respectively.