System dynamics baseline model for determining a multivariable objective function optimization in Wireless Sensor Networks

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferencia

Resumen

Wireless Sensor Networks (WSN) are dedicated networks used in applications where environmental information must be collected, such as temperature, humidity, level, flow, pressure, rain, radiation, among others. These kinds of networks are constrained regarding power, bandwidth, number of nodes per area unit, etc. It is desirable that they operate without supervision and can work steadily in time, because they are normally located in difficult or far places. Nonetheless, some of these metrics are conflicting with others, so if one improves, some of the others get worse. So, it is mandatory to know what is the best combination of metrics that in conjunction can fit an application the best. Literature reports works where \neg optimization is used as a mathematical scheme to solve this problem, and two scenarios are provided: First, where a single objective function is proposed regarding one metric, and the other metrics are restricted via constraints, and second, where multi-objective optimization (MOOP) approaches are proposed, but without considering the whole set of significant metrics involved in WSN, so there is not a definitive solution that finds a real optimal set of metrics. System Dynamics (SD) is a computer-aided approach to design and analyze (mostly) social, economic and enterprise systems, that allows proposing a mathematical framework to analyze such complex systems, by using relationships of interdependence, mutual interaction, feedback and causality. This work aims to show a first dynamic hypothesis of a model that considers important metrics ofWSN, in order to find a set of equations that serve as objective functions in a MOOP context. By applying this methodology is possible to find some difficult relations between metrics, that are not clearly reported by previous work so far.

Idioma originalInglés
Título de la publicación alojadaProceedings of CISTI 2020 - 15th Iberian Conference on Information Systems and Technologies
EditoresAlvaro Rocha, Bernabe Escobar Perez, Francisco Garcia Penalvo, Maria del Mar Miras, Ramiro Goncalves
EditorialIEEE Computer Society
ISBN (versión digital)9789895465903
DOI
EstadoPublicada - jun 2020
Evento15th Iberian Conference on Information Systems and Technologies, CISTI 2020 - Seville, Espana
Duración: 24 jun 202027 jun 2020

Serie de la publicación

NombreIberian Conference on Information Systems and Technologies, CISTI
Volumen2020-June
ISSN (versión impresa)2166-0727
ISSN (versión digital)2166-0735

Conferencia

Conferencia15th Iberian Conference on Information Systems and Technologies, CISTI 2020
PaísEspana
CiudadSeville
Período24/06/2027/06/20

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    Gonzalez-Palacio, M., Sepulveda-Cano, L., Valencia, J., D'Amato, J., Quiza-Montealegre, J., & Palacio, L. G. (2020). System dynamics baseline model for determining a multivariable objective function optimization in Wireless Sensor Networks. En A. Rocha, B. E. Perez, F. G. Penalvo, M. del Mar Miras, & R. Goncalves (Eds.), Proceedings of CISTI 2020 - 15th Iberian Conference on Information Systems and Technologies [9140915] (Iberian Conference on Information Systems and Technologies, CISTI; Vol. 2020-June). IEEE Computer Society. https://doi.org/10.23919/CISTI49556.2020.9140915