A modified differential evolution for autonomous deployment and localization of sensor nodes
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F11%3A86085024" target="_blank" >RIV/61989100:27240/11:86085024 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1145/2001858.2001990" target="_blank" >http://dx.doi.org/10.1145/2001858.2001990</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/2001858.2001990" target="_blank" >10.1145/2001858.2001990</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
A modified differential evolution for autonomous deployment and localization of sensor nodes
Popis výsledku v původním jazyce
The performance of a wireless sensor network (WSN) is largely influenced by the optimal deployment and accurate localization of sensor nodes. This article considers real-time autonomous deployment of sensor nodes from an unmanned aerial vehicle (UAV). This kind of deployment has importance, particularly in ad hoc WSNs, for emergency applications, such as disaster monitoring and battlefield surveillance. The objective is to deploy the nodes only in the terrains of interest, which are identified by segmentation of the images captured by a camera on board the UAV. In this article we propose an improved variant of an important evolutionary algorithm Differential Evolution for image segmentation and for distributed localization of the deployed nodes. Simulation results show that the proposed algorithm ADE_pBX performs image segmentation faster than both types of algorithm for optimal thresholds. Moreover in case of localization it gives more accurate results than the compared algorithms.
Název v anglickém jazyce
A modified differential evolution for autonomous deployment and localization of sensor nodes
Popis výsledku anglicky
The performance of a wireless sensor network (WSN) is largely influenced by the optimal deployment and accurate localization of sensor nodes. This article considers real-time autonomous deployment of sensor nodes from an unmanned aerial vehicle (UAV). This kind of deployment has importance, particularly in ad hoc WSNs, for emergency applications, such as disaster monitoring and battlefield surveillance. The objective is to deploy the nodes only in the terrains of interest, which are identified by segmentation of the images captured by a camera on board the UAV. In this article we propose an improved variant of an important evolutionary algorithm Differential Evolution for image segmentation and for distributed localization of the deployed nodes. Simulation results show that the proposed algorithm ADE_pBX performs image segmentation faster than both types of algorithm for optimal thresholds. Moreover in case of localization it gives more accurate results than the compared algorithms.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
IN - Informatika
OECD FORD obor
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Návaznosti výsledku
Projekt
<a href="/cs/project/GA102%2F09%2F1494" target="_blank" >GA102/09/1494: Nové metody přenosu dat založené na turbo kódech</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2011
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Genetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication
ISBN
978-1-4503-0690-4
ISSN
—
e-ISSN
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Počet stran výsledku
2
Strana od-do
235-236
Název nakladatele
ACM
Místo vydání
New York
Místo konání akce
Dublin
Datum konání akce
12. 7. 2011
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
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