Paper aceptado en el IOMAC’15 – Gijón
Posted on by frta

Las conferencias IOMAC’15 se celebrarán en Gijon, España, del 10 al 14 de Mayo de 2015.

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Estas ‘International Operational Modal Analysis Conference (IOMAC)‘, que nacieron en 2005, son las primeras conferencias que tienen como principal asunto el análisis modal operacional.

El paper que hemos presentado y que ha sido aceptado lleva por título:

“Effects of time synchronization on Operational Modal Analysis”

y cuyos autores han sido: Jaime García-Palacios, Francisco Tirado-Andrés, Jose M. Soria, Ivan M. Diaz y Alvaro Araujo.

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Anteriores ediciones del IOMAC se celebraron en:

  • 2005 Copenhagen (Denmark)
  • 2007 Copenhagen (Denmark)
  • 2009 Portonovo (Italy)
  • 2011 Istambul (Turkey)
  • 2013 Guimarães (Portugal)

Foto | Francisco Rodríguez

Artículo aceptado en la IWCMC 2015
Posted on by albarc

El artículo “Controlling the Degradation of Wireless Sensor Networks”, enmarcado en la tesis de Alba Rozas y cuyos co-autores son los miembros del B105 Javier Blesa, Elena Romero y Alvaro Araujo ha sido aceptado en la International Wireless Communications and Mobile Computing Conference (IWCMC 2015).

En el artículo se presentan varias de las ideas iniciales de la tesis de Alba Rozas, cuyo objetivo principal es el desarrollo de algoritmos y estrategias para el aumento del tiempo de vida de las redes de sensores. En concreto, se propone el concepto de “degradación controlada” para referirse a los mecanismos destinados a controlar el deterioro de calidad de servicio que sufren estas redes cuando se acercan al fin de su funcionamiento.

La conferencia tendrá lugar en Dubrovnik, Croacia, del 24 al 27 de agosto de 2015. Esperemos que sea una gran experiencia y sirva para obtener nuevas ideas y aportes a la investigación de esta tesis y del grupo en general.

Dubrovnik, Croacia

Cognitive Test-bed for Wireless Sensor Networks
Posted on by jblesa

Title: Cognitive Test-bed for Wireless Sensor Networks
Authors: Elena Romero, Javier Blesa, Agustín Tena, Guillermo Jara, Juan Domingo and Alvaro Araujo
Published in: IEEE DySPAN 2014
Date of Publication: March 2014
Web: http://dyspan2014.ieee-dyspan.org/

dyspanCognitive Wireless Sensor Networks are an emerging technology with a vast potential to avoid traditional wireless problems such as reliability, interferences and spectrum scarcity in Wireless Sensor Networks.

Cognitive Wireless Sensor Networks test-beds are an important tool for future developments,protocol strategy testing and algorithm optimization in real scenarios. A new cognitive test-bed for Cognitive Wireless Sensor Networks is presented in this paper. This work in progress includes the design of both a cognitive simulator for networks with high number of nodes and the implementation of a new platform with three wireless interfaces and a cognitive software for extracting real data.

Finally, as a future work, a remote programmable system and the planning for the physical deployment of the nodes at the university building is presented.

Cognitive Wireless Sensor Network Platform for Cooperative Communications
Posted on by b105

Title: Cognitive Wireless Sensor Network Platform for Cooperative Communications
Authors: Agustín Tena, Guillermo Jara, Juan Domingo, Elena Romero, Alvaro Araujo
Published in: International Journal of Distributed Sensor Networks
Date of Publication: January 2014
Digital Object Identifier : 10.1155/2014/473905
Web: http://www.hindawi.com/journals/ijdsn/2014/473905/

Nowadays, Wireless Ad-Hoc Sensor Networks (WAHSNs), specially limited in energy and resources, are subject to development constraints and difficulties such as the increasing Radio Frequency (RF) spectrum saturation at the unlicensed bands. Cognitive Wireless Sensor Networks (CWSNs), leaning on a cooperative communication model, develop new strategies to mitigate the inefficient use of the spectrum that WAHSNs face. However, few and poorly featured platforms allow their study due to their early research stage.

This paper presents a versatile platform that brings together cognitive properties into WAHSNs. It combines hardware and software modules as an entire instrument to investigate CWSNs. The hardware fits WAHSN requirements in terms of size, cost, features, and energy. It allows communication over three different RF bands, becoming the first cognitive platform for WAHSNs with this capability. In addition, its modular and scalable design is widely adaptable to almost any WAHSN application.

Significant features such as Radio Interface (RI) agility or energy consumption have been proved throughout different performance tests.

 

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PUE Attack Detection in CWSN Using Collaboration and Learning Behavior
Posted on by jblesa

Title: PUE Attack Detection in CWSN Using Collaboration and Learning Behavior
Authors: Javier Blesa, Elena Romero, Alba Rozas, Alvaro Araujo and Octavio Nieto-Taladriz
Published in: International Journal of Distributed Sensor Networks
Date of Publication: June 2013
Digital Object Identifier : 10.1155/2013/815959
Web: http://www.hindawi.com/journals/ijdsn/2013/815959/

Cognitive Wireless Sensor Network (CWSN) is a new paradigm which integrates cognitive features in traditional Wireless Sensor Networks (WSNs) to mitigate important problems such as spectrum occupancy. Security in Cognitive Wireless Sensor Networks is an important problem because these kinds of networks manage critical applications and data. Moreover, the specific constraints of WSN make the problem even more critical. However, effective solutions have not been implemented yet. Among the specific attacks derived from new cognitive features, the one most studied is the Primary User Emulation (PUE) attack. This paper discusses a new approach, based on anomaly behavior detection and collaboration, to detect the PUE attack in CWSN scenarios. A nonparametric CUSUM algorithm, suitable for low resource networks like CWSN, has been used in this work. The algorithm has been tested using a cognitive simulator that brings important results in this area. For example, the result shows that the number of collaborative nodes is the most important parameter in order to improve the PUE attack detection rates. If the 20% of the nodes collaborates, the PUE detection reaches the 98% with less than 1% of false positives.

cognitive radio module