Data replication in smart grids: Using genetic algorithms to build online partitioning schemes

Andreu Sancho-Asensio; Joan Navarro; Itziar Arrieta-Salinas; José Enrique Armendáriz-Íñigo; Elisabet Golobardes

Data replication in smart grids: Using genetic algorithms to build online partitioning schemes

Andreu Sancho-Asensio, Joan Navarro, Itziar Arrieta-Salinas, José Enrique Armendáriz-Íñigo, Elisabet Golobardes

Producción científica: Capítulo del libro › Contribución a congreso/conferencia › revisión exhaustiva

Resumen

With the growth of alternative energy sources and the poorly evolved power delivery infrastructures, Smart Grids are emerging as a feasible alternative to adapt electric networks to current demands. In contra- position to classic electrical architectures, Smart Grids encompass a fully distributed scheme with several data generation sources. Current data storage and replication systems fail at both coping with such overwhelming amount of heterogeneous data and satisfying the stringent requirements posed by this technology: dynamic nature of the physical resources, continuous ow of information and autonomous behavior demands. The purpose of this paper is to take advantage of soft computing strategies to face these challenges and, thus, present a hybrid system that mixes data replication and partitioning policies with genetic algorithms and unsupervised learning by means of an online approach. Conducted experiments show that the proposed system outperforms previous proposals and truly ts with the Smart Grid premises.

Idioma original	Inglés
Título de la publicación alojada	MENDEL 2013 - 19th International Conference on Soft Computing
Subtítulo de la publicación alojada	Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Fractals, Bayesian Methods
Editorial	Brno University of Technology
Páginas	7-12
Número de páginas	6
ISBN (versión impresa)	9788021447554
Estado	Publicada - 2013
Evento	19th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Fractals, Bayesian Methods, MENDEL 2013 - Brno, República Checa Duración: 26 jun 2013 → 28 jun 2013

Serie de la publicación

Nombre	Mendel
ISSN (versión impresa)	1803-3814

Conferencia

Conferencia	19th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Fractals, Bayesian Methods, MENDEL 2013
País/Territorio	República Checa
Ciudad	Brno
Período	26/06/13 → 28/06/13

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Sancho-Asensio, A., Navarro, J., Arrieta-Salinas, I., Armendáriz-Íñigo, J. E., & Golobardes, E. (2013). Data replication in smart grids: Using genetic algorithms to build online partitioning schemes. En MENDEL 2013 - 19th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Fractals, Bayesian Methods (pp. 7-12). (Mendel). Brno University of Technology.

Sancho-Asensio, Andreu ; Navarro, Joan ; Arrieta-Salinas, Itziar et al. / Data replication in smart grids : Using genetic algorithms to build online partitioning schemes. MENDEL 2013 - 19th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Fractals, Bayesian Methods. Brno University of Technology, 2013. pp. 7-12 (Mendel).

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title = "Data replication in smart grids: Using genetic algorithms to build online partitioning schemes",

abstract = "With the growth of alternative energy sources and the poorly evolved power delivery infrastructures, Smart Grids are emerging as a feasible alternative to adapt electric networks to current demands. In contra- position to classic electrical architectures, Smart Grids encompass a fully distributed scheme with several data generation sources. Current data storage and replication systems fail at both coping with such overwhelming amount of heterogeneous data and satisfying the stringent requirements posed by this technology: dynamic nature of the physical resources, continuous ow of information and autonomous behavior demands. The purpose of this paper is to take advantage of soft computing strategies to face these challenges and, thus, present a hybrid system that mixes data replication and partitioning policies with genetic algorithms and unsupervised learning by means of an online approach. Conducted experiments show that the proposed system outperforms previous proposals and truly ts with the Smart Grid premises.",

keywords = "Data partitioning, Data replication, Genetic algorithms, Multi-agent systems, Unsupervised learning",

author = "Andreu Sancho-Asensio and Joan Navarro and Itziar Arrieta-Salinas and Armend{\'a}riz-{\'I}{\~n}igo, {Jos{\'e} Enrique} and Elisabet Golobardes",

year = "2013",

language = "English",

isbn = "9788021447554",

series = "Mendel",

publisher = "Brno University of Technology",

pages = "7--12",

booktitle = "MENDEL 2013 - 19th International Conference on Soft Computing",

note = "19th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Fractals, Bayesian Methods, MENDEL 2013 ; Conference date: 26-06-2013 Through 28-06-2013",

}

Sancho-Asensio, A, Navarro, J, Arrieta-Salinas, I, Armendáriz-Íñigo, JE & Golobardes, E 2013, Data replication in smart grids: Using genetic algorithms to build online partitioning schemes. En MENDEL 2013 - 19th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Fractals, Bayesian Methods. Mendel, Brno University of Technology, pp. 7-12, 19th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Fractals, Bayesian Methods, MENDEL 2013, Brno, República Checa, 26/06/13.

Data replication in smart grids: Using genetic algorithms to build online partitioning schemes. / Sancho-Asensio, Andreu; Navarro, Joan; Arrieta-Salinas, Itziar et al.
MENDEL 2013 - 19th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Fractals, Bayesian Methods. Brno University of Technology, 2013. p. 7-12 (Mendel).

Producción científica: Capítulo del libro › Contribución a congreso/conferencia › revisión exhaustiva

TY - GEN

T1 - Data replication in smart grids

T2 - 19th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Fractals, Bayesian Methods, MENDEL 2013

AU - Sancho-Asensio, Andreu

AU - Navarro, Joan

AU - Arrieta-Salinas, Itziar

AU - Armendáriz-Íñigo, José Enrique

AU - Golobardes, Elisabet

PY - 2013

Y1 - 2013

N2 - With the growth of alternative energy sources and the poorly evolved power delivery infrastructures, Smart Grids are emerging as a feasible alternative to adapt electric networks to current demands. In contra- position to classic electrical architectures, Smart Grids encompass a fully distributed scheme with several data generation sources. Current data storage and replication systems fail at both coping with such overwhelming amount of heterogeneous data and satisfying the stringent requirements posed by this technology: dynamic nature of the physical resources, continuous ow of information and autonomous behavior demands. The purpose of this paper is to take advantage of soft computing strategies to face these challenges and, thus, present a hybrid system that mixes data replication and partitioning policies with genetic algorithms and unsupervised learning by means of an online approach. Conducted experiments show that the proposed system outperforms previous proposals and truly ts with the Smart Grid premises.

AB - With the growth of alternative energy sources and the poorly evolved power delivery infrastructures, Smart Grids are emerging as a feasible alternative to adapt electric networks to current demands. In contra- position to classic electrical architectures, Smart Grids encompass a fully distributed scheme with several data generation sources. Current data storage and replication systems fail at both coping with such overwhelming amount of heterogeneous data and satisfying the stringent requirements posed by this technology: dynamic nature of the physical resources, continuous ow of information and autonomous behavior demands. The purpose of this paper is to take advantage of soft computing strategies to face these challenges and, thus, present a hybrid system that mixes data replication and partitioning policies with genetic algorithms and unsupervised learning by means of an online approach. Conducted experiments show that the proposed system outperforms previous proposals and truly ts with the Smart Grid premises.

KW - Data partitioning

KW - Data replication

KW - Genetic algorithms

KW - Multi-agent systems

KW - Unsupervised learning

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M3 - Conference contribution

AN - SCOPUS:84905735851

SN - 9788021447554

T3 - Mendel

SP - 7

EP - 12

BT - MENDEL 2013 - 19th International Conference on Soft Computing

PB - Brno University of Technology

Y2 - 26 June 2013 through 28 June 2013

ER -

Sancho-Asensio A, Navarro J, Arrieta-Salinas I, Armendáriz-Íñigo JE, Golobardes E. Data replication in smart grids: Using genetic algorithms to build online partitioning schemes. En MENDEL 2013 - 19th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Fractals, Bayesian Methods. Brno University of Technology. 2013. p. 7-12. (Mendel).

Data replication in smart grids: Using genetic algorithms to build online partitioning schemes

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