DISEÑO Y DESPLIEGUE DE UNA RED INALÁMBRICA DE SENSORES COGNITIVA, ROBUSTA Y ESCALABLE

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Durante los últimos años se ha observado un notable incremento en la penetración de las redes inalámbricas en nuestra sociedad, teniendo previsiones de crecimiento bastante elevadas con la irrupción de Internet de las Cosas (IoT). Sin embargo, esta interconexión masiva desemboca en la aparición de problemas como son principalmente la saturación del espectro radioeléctrico o las interferencias provocadas entre sistemas, lo que repercute en la calidad del servicio y por lo tanto supone un problema para la conexión de elementos.

El B105 lab tiene como una de sus líneas principales de investigación el desarrollo de redes inalámbricas de sensores cognitivas (CWSN, Cognitive Wireless Sensor Networks), es decir, redes compuestas por dispositivos con la capacidad de modificar sus parámetros de comunicación dinámicamente, seleccionando las zonas del espectro con menos ruido e interferencias y por consiguiente, capaces de optimizar las prestaciones globales de la red.

Proyectos anteriores se centraron en el estudio de estos dispositivos, desarrollando la plataforma cNGD (cognitive New Generation Device). Se trata de un nodo que incluye la torre de protocolos de Microchip, que fue modificada para poder albergar tres transceptores radio, consiguiendo trabajar simultáneamente en las bandas de libre acceso de 434, 868 y 2400 MHz.

Plataforma cNGD sobre la que se ha trabajado
Plataforma cNGD sobre la que se ha trabajado

Este Trabajo Fin de Grado los adopta como base y se centra en diseñar e implementar distintas funcionalidades en la actual pila de protocolos, con el objetivo de conseguir interconectar varios cNGDs bajo un modelo de red de tipo malla fiable, robusto y escalable. Estos mecanismos se deben adaptar al tipo de dispositivo, el orden de su llegada a la red y a la frecuencia de trabajo.  Los principales requisitos que se han impuesto en el diseño de la red son:

  • Aceptar a todos los dispositivos que deseen incorporarse mientras la red disponga de capacidad para registrarlos.
  • Garantizar la unicidad en la asignación de la direcciones de red,  para posteriormente, poder realizar correctamente el encaminamiento de paquetes.
  • Que los coordinadores de red sepan reaccionar ante variaciones en la estructura de la red (principalmente conexión y desconexión de coordinadores).
  • Asegurar un máximo de 4 saltos en el encaminamiento de paquetes hasta alcanzar al destinatario.
  • Otros: Inclusión de mecanismos de fiabilidad en las transmisiones de mensajes, no inundar la red con la emisión de paquetes broadcast o informar a las capas superiores del éxito o fracaso en la realización de las operaciones.

Tras la etapa de implementación, modificación y adaptación del software del cNGD, se ha procedido a desplegar la red, midiendo y analizando los resultados obtenidos. Efectivamente, se han cumplido los requisitos impuestos, es decir, se ha conseguido la interconexión de varios cNGDs bajo un modelo de red robusto y fiable, que puede servir de soporte para futuras líneas de trabajo que se centren en las capas de aplicación o en la capa cognitiva del cNGD.

 

Thesis: Software-Defined Radio Techniques for Resource Optimization in Cognitive Wireless Sensor Networks

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Author: Ramiro Utrilla Gutiérrez

Advisor: Alvaro Araujo Pinto

Synopsis: Due to the spectrum scarcity problem, mostly in license-free ISM bands, and the forecasts regarding the increasing adoption of wireless communications, especially in scenarios like cities, it is essential to optimize the use of the spectrum to ensure the proper functioning of services and devices in the near future.

As the characteristics of the spectrum, by their own physical nature and its use, are very dynamic and vary constantly, devices must be able to intelligently adapt to these changes, as the Cognitive Radio paradigm proposes. Moreover, this adaptation should be done quickly in order to be effective and it should minimize the impact on the use of the spectrum.

Because of that, this work is going to be mainly focused on the development and evaluation of cognitive strategies with zero or minimum communication overhead. In other words, the aim of the research is to evaluate the degree of optimization of resources that can be achieved in a Cognitive Wireless Sensor Network (CWSN) by doing the cognitive cycle (spectrum sensing, learning and adaptation) mostly at node-level. To better exploit the cognitive radio capabilities of these networks, and thanks to the current development of wireless and processing technology, Software-Defined Radio (SDR) techniques are going to be used in sensor nodes for that purpose. This approach supposes a new paradigm in CWSNs which implies new challenges to be faced.

At this point, it appears to be necessary to evaluate some issues about the future of wireless communications. Will someday the need for cognition to use the spectrum outweigh the current energy constraints? In other words, will it be possible to achieve efficient and reliable wireless communication without cognitive capabilities in the near future? Answering this question will reveal whether it still make sense to compare the power consumption of SDR solutions with other platforms based on COTS radio transceivers or, conversely, the addition of cognitive capabilities will cease to pose a challenge to maximize systems’ efficiency and become a key point for their proper operation.

 

Despliegue de un banco de pruebas para CWSN

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El objetivo de este Proyecto Fin de Carrera es el despliegue de un banco de pruebas para una red de sensores cognitiva (CWSN). Esta red contará con varios nodos cognitivos que permitirán la prueba de estrategias de optimización en este tipo de redes. Este banco de pruebas se realizará contando con una serie de nodos cognitivos previamente desarrollados en el laboratorio (cNGD) sobre el que se han hecho varios desarrollos software para adaptar tanto el protocolo de comunicación radio como la arquitectura cognitiva.

El despliegue del banco de pruebas cubrirá todas las salas permitidas del laboratorio B105 y el Departamento de Ingeniería Electrónica. Este proyecto abarca tanto la planificación del montaje físico de los nodos como el desarrollo de una interfaz para la gestión y recolección de información del banco de pruebas. Algunos parámetros a tener en cuenta serán el alcance de los nodos, su accesibilidad o la fuente de alimentación.

Tecnologías relacionadas

  • Cognitive Radio
  • Wireless Sensor Networks
  • Linux
  • C
  • Diseño Hardware

Tutor

Javier Blesa <jblesa@die.upm.es>
Elena Romero <elena@die.upm.es>

Status

Sin asignar

Cognitive Wireless Sensor Network Platform for Cooperative Communications

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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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B105 Media Lab

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logob105media

B105 is proud to present its brand new Youtube Channel: B105 MediaLab.
The initiative arises as a new way to show the world how life is at B105, who we are and what kind of activities are carried out in our lab.

We will be uploading videos about a wide range of topics, from public talks and tutorials to more specific R&D presentations. By now, we have prepared the following videos for the channel’s setting up.

IntroTutorialGit

1) GIT tutorial:
A thorough introduction to GIT, the popular software repository.  Starting from the scratch, Fernando López gives an insight into the design, functioning and basic use of this tool, illustrating some issues with examples and answering some attendants’ questions.

TituloCNGD

2) cNGD demo:
As part of the research in Cognitive Radio and WSN, Agustín Tena finished his Telecommunication Engineering studies presenting the hardware platform for the cognitive New Generation Device (cNGD). The video is a communication demo between two cNGD nodes which was part of his final degree project (PFC) dissertation.

We hope you to find these videos interesting, entertaining and useful. Subscribe to B105 Media Lab!!

An Architecture’s Desing and Implementation for Communications Management in a Cognitive Wireless Sensor Network

Cognitive radio communications

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The objective of this project is to design and develop a software architecture that will be able to implement cognitive strategies in nodes to conform a CWSN.

The main model this architecture follows is that one proposed in the Connectivity Brokerage (Jan Rabaey, Adam Wolisz, Ali Ozer Ercan, Alvaro Araujo, Fred Burghardt, Samah Mustafa, Arash Parsa, Sofie Pollin, I-Hsiang Wang, Pedro Malagon 2010) and is represented as follows:

CRModule

In the figure above six modules are shown inside the CAgent (Cognitive Agent). Each of this modules play an specific role inside the Cognitive Module and the work of all of them makes possible the execution of the Cognitive Cycle as defined in Cognitive Networks (Ryan W. Thomas, Luiz A. DaSilva, Allen B. MacKenzie 2005) which exposes that: “A cognitive network has a cognitive process that can perceive current network conditions, and then plan, decide and act on those conditions. The network can learn from these adaptations and use them to make future decisions, all while taking into account end-to-end goals.”.

Related Technologies

  • Cognitive Radio
  • Wireless Sensor Networks
  • Hardware design
  • C programming

Task

  • State of the art study in cognitive networks
  • Requirements definition
  • Architecture design
  • Hardware design
  • Software implementation
  • Tests and results

Tutor

Alvaro Araujo <araujo@die.upm.es>

State

In progress

Thesis: Cognitive strategies for reducing energy consumption in Wireless Sensor Networks

Cognitive strategies energy

 

Author: Elena Romero Perales

Advisor: Alvaro Araujo Pinto

Synopsis: Global data traffic in telecommunication annually grows with a rate higher than 50%. While the growth in traffic is stunning, the rapid adoption of wireless technology over the complete globe and the penetration through all layers of society is even more amazing. Over the span of 20 years, wireless subscription has risen to 40% of the world population, and is expected to grow to 70% by 2015. Overall mobile data traffic is expected to grow to 6.3 exabytes per month by 2015, a 26-fold increase over 2010. This expansion leads to an increase of the energy consumption by approximately 10% per year. A major portion of this expanding traffic has been migrating to mobile networks and systems. Due to this growth in wireless data traffic, the associated consumption to it becomes very important. Up to now, wireless network power consumption has not been an important issue because it was insignificant in comparison with wired network consumption. Nevertheless, over the recent years, wireless and mobile communications are increasingly becoming popular with consumer. Take into account the wireless traffic prediction the current rate of power consumption per unit of data cannot be sustained.

One of the most important trends related with the expansion of wireless networks is the significant increase of ubiquitous computing. WSNs give technological solution to this challenge, so its growth is closely linked to these data. Typical ubiquitous applications include security and surveillance (sensor nodes and video streams transmitted by Wi-Fi), health care (medical information transmitted by sensor nodes) or vehicular networks. Due to the number of nodes, its wireless nature, and its deployment in difficult access areas, WSN nodes should not require any maintenance. In terms of consumption this means that the sensors must be energetically autonomous and therefore the batteries cannot be changed or recharged.

The increasing demand for wireless communication presents an efficient spectrum utilization challenge. To address this challenge, Cognitive Radio (CR) has emerged as the key technology, which enables opportunistic access to the spectrum. In this way, the cooperation between devices introducing by CR regarding information sharing and taking decisions allows better spectrum use, lower energy consumption and better data reliability. The introduction of Cognitive Radio capabilities in WSN provides a new paradigm for power consumption reduction offering new opportunities to improve it, but also implies some challenges to face. Talking in detail about power consumption, sensing state, collaboration among devices (that requires communication) and changes in transmission parameters are not free in terms of consumption. In this way, all steps must be taken into account for a holistic optimization. Reducing power consumption requires optimization across all the layers of the communication systems.

 The final goal is to reduce energy consumption in WSN exploiting the new capabilities introduced by the cognitive radio concept.