Distributed clustering algorithm for spatial field reconstruction in wireless sensor networks
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Distributed clustering algorithm for spatial field reconstruction in wireless sensor networks

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Distributed clustering algorithm for spatial field reconstruction in wireless sensor networks

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dc.contributor.author Chowdappa, Vinay-Prasad
dc.contributor.author Botella Mascarell, Carmen
dc.contributor.author Beferull-Lozano, Baltasar
dc.date.accessioned 2021-08-23T08:14:55Z
dc.date.available 2021-08-24T04:45:05Z
dc.date.issued 2015 es_ES
dc.identifier.uri https://hdl.handle.net/10550/80121
dc.description.abstract En este trabajo, consideramos el problema de la estimación espacial distribuida para la reconstrucción del campo radio en redes de sensores inalámbricos. Para estimar el campo, se utiliza una técnica geoestadística llamada kriging. La estimación espacial centralizada con un gran número de sensores conllevan un elevado coste computacional y gasto de energía. Presentamos un novedoso algoritmo de clustering distribuido para estimar mapas de interferencia espacial, que son esenciales para las operaciones y la gestión de las futuras redes inalámbricas. En este algoritmo, los clústeres de sensores se forman de forma adaptativa mediante la minimización de la varianza de kriging. El cálculo del semivariograma y la predicción de kriging se realizan localmente en cada clúster de forma distribuida. Se analiza la complejidad del algoritmo de clustering y se evalúa su rendimiento comparándolo con enfoques centralizados y otros enfoques distribuidos. es_ES
dc.description.sponsorship GRISOLIA/2012/028; CONSOLIDER-INGENIO 2010 CSD 2008-00010 COMONSENS; RACHEL TEC2013-47141-C4-4- R; European STREP Project HYDROBIONETS Grant no. 287613 es_ES
dc.language.iso en es_ES
dc.source V. Chowdappa, C. Botella and B. Beferull-Lozano, "Distributed Clustering Algorithm for Spatial Field Reconstruction in Wireless Sensor Networks," 2015 IEEE 81st Vehicular Technology Conference (VTC Spring), 2015, pp. 1-6 es_ES
dc.subject spatial field reconstruction es_ES
dc.subject wireless sensor networks es_ES
dc.subject clustering es_ES
dc.subject kriging es_ES
dc.title Distributed clustering algorithm for spatial field reconstruction in wireless sensor networks es_ES
dc.type info:eu-repo/semantics/article es_ES
dc.subject.unesco UNESCO::CIENCIAS TECNOLÓGICAS es_ES
dc.identifier.doi https://doi.org/10.1109/VTCSpring.2015.7145783 es_ES
dc.description.abstractenglish In this paper, we consider the problem of distributed spatial estimation for field reconstruction in wireless sensor networks. In order to estimate the field, a geostatistical technique called kriging is used. Centralized spatial estimation algorithms with a large number of sensors lead to significant computational cost and energy wastage. We present a novel distributed clustering algorithm for estimating spatial interference maps, which are essential for operations and management in future wireless networks. In this algorithm, clusters are adaptively formed with a small subset of sensors by minimizing the kriging variance. The semivariogram computation and kriging prediction are locally performed in each cluster in a distributed fashion. The complexity of the clustering algorithm is analyzed and its performance is evaluated by comparing it with centralized and other distributed approaches. es_ES
dc.accrualMethod - es_ES
dc.embargo.terms 0 days es_ES

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