A lightweight indoor localization model based on motley-keenan and COST

This paper presents a novel approach to WLAN propagation models for use in indoor localization. The major goal of this work is to eliminate the need for in situ data collection to generate the Fingerprinting map, instead, it is generated by using analytical propagation models such as: COST Multi-Wall, COST 231 average wall and Motley- Keenan. As Location Estimation Algorithms kNN (K-Nearest Neighbour) and WkNN (Weighted K-Nearest Neighbour) were used to determine the accuracy of the proposed technique. This work is based on analytical and measurement tools to determine which path loss propagation models are better for location estimation applications, based on Receive Signal Strength Indicator (RSSI).This study presents different proposals for choosing the most appropriate values for the models parameters, like obstacles attenuation and coefficients. Some adjustments to these models, particularly to Motley-Keenan, considering the thickness of walls, are proposed. The best found solution is based on the adjusted Motley-Keenan and COST models that allows to obtain the propagation loss estimation for several environments.Results obtained from two testing scenarios showed the reliability of the adjustments, providing smaller errors in the measured values values in comparison with the predicted values.

Sistema de localização indoor com base no protocolo ZIGBEE

Actualmente, os sistemas de localização são uma área em forte expansão sendo que para espaços exteriores existe uma grande variedade de sistemas de localização enquanto que para espaços interiores as soluções são mais escassas. Este trabalho apresenta o estudo e implementação de um sistema de localização indoor baseado no protocolo ZigBee, utilizando a informação da intensidade de sinal recebido (RSSI - Received Signal Strength Indication). Para a realização deste projecto foi necessário iniciar uma pesquisa mais pormenorizada do protocolo ZigBee. O dispositivo móvel a ser localizado é o módulo XBee Serie 2 que se baseia no mesmo protocolo. Posto isto, foi necessário efectuar um estudo sobre sistemas de localização existentes e analisar as técnicas de localização utilizadas para ambientes interiores. Desta forma utiliza-se neste projecto uma técnica que consiste na análise de fingerprinting, onde é criado um mapa com os valores RSSI para diferentes coordenadas do espaço físico. As intensidades de sinal recebido são relativas a dispositivos XBee instalados em pontos fixos de referência. Para calcular a localização do dispositivo móvel é utilizado o algoritmo K-NN (K- Nearest Neighbors) que permite estimar a posição aproximada do dispositivo móvel. Por último é descrito todo o desenvolvimento do projecto assim como a apresentação e discussão de resultados.

Reliable link quality estimation in low-power wireless networks and its impact on tree-routing

Radio link quality estimation is essential for protocols and mechanisms such as routing, mobility management and localization, particularly for low-power wireless networks such as wireless sensor networks. Commodity Link Quality Estimators (LQEs), e.g. PRR, RNP, ETX, four-bit and RSSI, can only provide a partial characterization of links as they ignore several link properties such as channel quality and stability. In this paper, we propose F-LQE (Fuzzy Link Quality Estimator, a holistic metric that estimates link quality on the basis of four link quality properties—packet delivery, asymmetry, stability, and channel quality—that are expressed and combined using Fuzzy Logic. We demonstrate through an extensive experimental analysis that F-LQE is more reliable than existing estimators (e.g., PRR, WMEWMA, ETX, RNP, and four-bit) as it provides a finer grain link classification. It is also more stable as it has lower coefficient of variation of link estimates. Importantly, we evaluate the impact of F-LQE on the performance of tree routing, specifically the CTP (Collection Tree Protocol). For this purpose, we adapted F-LQE to build a new routing metric for CTP, which we dubbed as F-LQE/RM. Extensive experimental results obtained with state-of-the-art widely used test-beds show that F-LQE/RM improves significantly CTP routing performance over four-bit (the default LQE of CTP) and ETX (another popular LQE). F-LQE/RM improves the end-to-end packet delivery by up to 16%, reduces the number of packet retransmissions by up to 32%, reduces the Hop count by up to 4%, and improves the topology stability by up to 47%.

Impact of sensor nodes scaling and velocity on handover mechanisms for healthcare wireless sensor networks with mobility support

Health promotion in hospital environments can be improved using the most recent information and communication technologies. The Internet connectivity to small sensor nodes carried by patients allows remote access to their bio-signals. To promote these features the healthcare wireless sensor networks (HWSN) are used. In these networks mobility support is a key issue in order to keep patients under realtime monitoring even when they move around. To keep sensors connected to the network, they should change their access points of attachment when patients move to a new coverage area along an infirmary. This process, called handover, is responsible for continuous network connectivity to the sensors. This paper presents a detailed performance evaluation study considering three handover mechanisms for healthcare scenarios (Hand4MAC, RSSI-based, and Backbone-based). The study was performed by simulation using several scenarios with different number of sensors and different moving velocities of sensor nodes. The results show that Hand4MAC is the best solution to guarantee almost continuous connectivity to sensor nodes with less energy consumption.

Sistema de posicionamento baseado em redes de sensores sem fios

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores

Sensoriteknologia rakennetun alueen taistelussa

Nykyajan sodankäynti painottuu yhä enemmän taisteluun informaatiosta. Informaation perusteella muodostetaan tilannekuva, jonka avulla päätökset tehdään. Informaation hankinnassa on sensoriteknologia keskeisessä asemassa. Kaupunkien merkityksen korostumisen seurauksena pääosa nykyajan taisteluista tullaan käymään ainakin osittain rakennetulla alueella. Sensorien toiminnan kannalta rakennettu alue on aivan erilainen ympäristö kuin esimerkiksi metsämaasto. Esimerkiksi lyhyet tähystysetäisyydet erityisesti sisätiloissa, rajoitettu näkyvyys, erilaisista materiaaleista valmistetut rakennukset ja pinnat sekä valoisuuden vaihtelu sisätiloissa asettavat uusia vaatimuksia sensorien suorituskyvylle. Tutkimuksessa tarkastellaan uhkamallina Yhteiskunnan turvallisuusstrategian mukaista strategista iskua, jonka osakohteina voivat olla esimerkiksi sähkön jakelun valvomot ja materiaalin varastotilat. Näiden kohteiden lisäksi tarkastellaan ulkotiloja yleisesti. Tutkimus on kirjallisuustutkimus ja sen tarkastelutapa on tekninen. Tutkimuksen ensimmäisen osan tarkoituksena on selvittää eri sensoreiden suorituskyky ja kehityksen tulevaisuudennäkymiä. Tutkimuksen toisessa osassa tarkastellaan eri sensorijärjestelmien sopivuutta tilannekuvan hankkimiseen ja ylläpitoon rakennetulla alueella kahta esimerkkitapausta soveltaen. Tavoitteena on selvittää rakennetun alueen asettamat reunaehdot eri sensorijärjestelmille. Tutkimuksen tulokset osoittavat, että yksittäiseen teknologiaan perustuva sensori ei ole suorituskykyinen rakennetulla alueella. Eri teknologiat soveltuvat eri olosuhteisiin ja monien nykyisten järjestelmien suorituskyky rakennetulla alueella on hyvin rajoittunut. Tutkimuksen perusteella tulevaisuudessa korostuvat erityisesti optronisten sensorien integrointi yhteen laitteeseen, liikuteltavat sensorit sekä langattomat sensoriverkot. Sensoriteknologia rakennetulla alueella vaatii runsaasti lisätutkimusta esimerkiksi sensorin lavetin merkityksestä ja taistelunkestävyydestä sekä taktisten miehittämättömien ilmaalusten käytöstä sisä- ja ulkotiloissa.

Kurkistuksia Suomeen

Kirjallisuusarvostelu

Monitorização ambiental em espaços florestais com rede de sensores sem fios

O objectivo deste projecto é desenvolver um sistema de monitorização florestal recorrendo às Redes de Sensores sem Fios. Para a monitorização florestal foi desenvolvido um protótipo cuja função é obter periodicamente os valores de temperatura, humidade, luminosidade, tensão nas baterias e a indicação do nível de sinal de rádio frequência recebido (RSSI- Received Signal Strength Indicator). O equipamento referido foi instalado num ambiente exterior, com características semelhantes à de interesse de modo a permitir avaliar os efeitos do ambiente no desempenho da rede. O funcionamento das Redes de Sensores sem Fios, baseadas no protocolo ZigBee, foi estudado e depois aplicado para transmitir os valores obtidos. Os dados referidos percorrem a rede ZigBee até alcançar a estação base, que tem como função processar, manipular, armazenar numa base de dados e disponibilizar os dados em tempo real através de uma página de Internet. Como os dados são armazenados é sempre possível efectuar uma consulta à base de dados para realização de estudos e estatísticas. Tendo em conta a capacidade limitada dos sistemas de armazenamento de energia utilizados em ambientes exteriores, foi desenvolvido um algoritmo que permite comutar os dispositivos na rede ZigBee de router para end-device e vice-versa, de modo a diminuir o consumo de energia e aumentar o tempo de vida da rede. Este algoritmo foi testado numa situação em que os nós sensores estão colocados em linha, existindo um único salto entre os mesmos.

Monitorização de provas de educação física

O presente trabalho tem por objectivo desenvolver um sistema de monitorização de provas de educação física e do ambiente circundante. Neste projecto desenvolveu-se um protótipo para uma Rede de Sensores Sem Fios (RSSF) que realiza a monitorização, em tempo real, do esforço e desempenho da actividade física dos atletas e das características físicas do ambiente. Estudou-se o funcionamento das RSSF, baseadas no protocolo ZigBee, e foram desenvolvidos módulos de monitorização de atletas e ambiente que integram esta tecnologia como meio de comunicação. O módulo de monitorização de atletas é composto por acelerómetro, sensor de batimento cardíaco e GPS. Inclui um serviço de localização secundário a partir do received signal strenght indicator (RSSI) caso o serviço de GPS estiver indisponível. O módulo de monitorização ambiental é composto por vários sensores que monitorizam: humidade, temperatura, luminosidade, monóxido de carbono, dióxido de carbono e oxigénio. Cada módulo de monitorização ambiental foi munido com Bluetooth, por forma a que os atletas, sempre que no alcance da rede, possam com o próprio telemóvel consultar o valor actual dos parâmetros ambientais e a sua localização. Estes dados são medidos e transmitidos periodicamente, em tempo real, pela rede ZigBee para uma estação base acoplada a um computador. Os dados são armazenados e processados e os resultados são disponibilizados através de uma aplicação no computador local e de uma página na Internet. Neste trabalho verifica-se que a RSSF, que utiliza o protocolo ZigBee, é capaz de realizar comunicação entre atletas, sensores ambientais e computador com baixo consumo energético, optimizando a autonomia pretendida. Este sistema de RSSF integrado com a tecnologia sensorial actual, permite o desenvolvimento de módulos com um elevado nível de funcionalidades em dimensões relativamente reduzidas.

BlueFriends: measuring, analyzing and preventing social exclusion between elementary school students

Social exclusion is a relatively recent term, whose creation is attributed to René Lenoir(Lenoir, 1974). Its concept covers a remarkably wide range of social and economic problems, and can be triggered for various reasons: mentally and physically handicapped, abused children, delinquents, multi-problem households, asocial people, and other social “misfits” (Silver, 1995, pp. 63; Foucault, 1992). With an increasingly multi-cultural population, cultural and social inequalities rapidly ascend, bringing with them the need for educational restructuring. We are living in an evermore diverse world, and children need to be educated to be receptive to the different types of people around them, especially considering social and cultural aspects. It is with these goals that inclusive education has seen an increased trend in today’s academic environment, reminding us that even though children may be taught under the same roof, discriminatory practices might still happen. There are, however, a number of developed tools to assess the various dimensions of social networks. These are mostly based on questionnaires and interviews, which tend to be fastidious and don’t allow for longitudinal, large scale measurement. This thesis introduces BlueFriends, a Bluetooth-based measurement tool for social inclusion/exclusion on elementary school classes. The main goals behind the development of this tool were a) understanding how exclusion manifests in students’ behaviors, and b) motivating pro-social behaviors on children through the use of a persuasive technology. BlueFriends is a distributed application, comprised by an application running on several smartphones, a web-hosted database and a computer providing a visual representation of the data collected on a TV screen, attempting to influence children behaviors. The application makes use of the Bluetooth device present on each phone to continuously sample the RSSI (Received Signal Strength Indication) from other phones, storing the data locally on each phone. All of the stored data is collected, processed and then inserted into the database at the end of each day. At the beginning of each recess, children are reminded of how their behaviors affect others with the help of a visual display, which consists of interactions between dogs. This display illustrates every child’s best friends, as well as which colleagues they don’t interact with as much. Several tips encouraging social interaction and inclusiveness are displayed, inspiring children to change their behaviors towards the colleagues they spend less time with. This thesis documents the process of designing, deploying and analyzing the results of two field studies. On the first study, we assess how the current developed tools are inferior to our measuring tool by deploying a measurement only study, aimed at perceiving how much information can be obtained by the BlueFriends application and attempting to understand how exclusion manifests itself in the school environment. On the second study, we pile on the previous to try and motivate pro-social behaviors on students, with the use of visual cues and recommendations. Ultimately, we confirm that our measurement tool’s results were satisfying towards measuring and changing children’s behaviors, and conclude with our thoughts on possible future work, suggesting a number of possible extensions and improvements.

Indoor position, localizzazione e tracciamento in ambienti chiusi

Le grandi catene di distribuzione, per sviluppare strategie commerciali sempre più efficaci, sono interessate a comprendere il percorso che ogni cliente effettua all’interno del punto vendita, che reparti visita, il tempo di permanenza in un’area specifica ecc… Quindi è stato necessario trovare un sistema per localizzare e tracciare un cliente all’interno di un ambiente chiuso (indoor position). Prima di tutto ci si è concentrati sulla ricerca e sviluppo di una nuova idea che potesse superare gli ostacoli delle soluzioni attualmente in commercio. Si è pensato di sostituire le tessere punti del punto vendita con delle tessere bluetoothLE e di creare un sistema di posizionamento al chiuso utilizzando la stessa logica di funzionamento del GPS per gli ambienti aperti. Il ricevitore è la tessera BLE posseduta dal cliente e i satelliti sono tre device Android dotati di un’app specifica per rilevare il segnale radio (RSSI) emesso dalla tessera ogni secondo. Le rilevazioni dei tre device Android sono successivamente trasferite all’interno di una web application che si occupa di elaborare i dati tramite il processo di trilaterazione. L’output sono le coordinate x,y di ciascuna tessera in ogni secondo di visita all’interno del punto vendita. Questi dati sono infine utilizzati per mostrare graficamente il percorso effettuato dal cliente, l’orario di ingresso e di uscita e il tempo di permanenza. Riepilogando, il progetto comprende una fase di ricerca e intuizione di una nuova idea, una fase di progettazione per traslare i meccanismi del funzionamento GPS all’utilizzo in un ambiente chiuso, una fase di implementazione dell’app e della web application e infine una fase di sperimentazioni sul campo che si concluderà dopo la laurea con test reali in un supermercato della zona.

Progettazione ed Implementazione di un sistema di localizzazione di oggetti tramite Beacon

In questo elaborato viene descritto il funzionamento dei Beacon. Essi rappresentano un congegno che sfrutta la tecnologia Bluetooth 4.0, la quale, rispetto alle precedenti, si differenzia per alcune innovazioni apportate. Il loro utilizzo originario era rivolto al mondo del Mobile Advertising, ovvero l’invio di messaggi ad hoc agli utenti, sulla base di studi mirati a personalizzare un contenuto. Con lo scorrere del tempo invece si sono cercate nuove modalità d'uso in relazione al mondo da cui derivano: L'”Internet of Things” (IoT). Questa espressione descrive l'intento di dare vita agli oggetti. L'obiettivo di fondo è stato quello di delineare uno dei possibili casi d'uso. Nel concreto il sistema si prefigge, sfruttando l’interazione tra gli utenti, di monitorare la posizione in ambienti indoor di oggetti, usando il segnale RSSI dei Beacon ai quali sono associati, fornire l’aggiornamento dell’indirizzo in cui sono situati, visualizzabile sulle mappe Google con cui l’app è collegata, notificare ai proprietari gli eventuali ritrovamenti di uno di essi, rintracciare i dispositivi altrui. Prima di ciò, si è svolta un'analisi inerente le prestazioni che i Beacon sono in grado di offrire, in condizioni normali, prestando attenzione ad alcuni parametri come: frequenza di trasmissione (l’intervallo entro il quale vengono emessi segnali), il periodo di scansione (l’effettivo periodo di attività), più un’altra serie di risultati acquisiti durante l'esecuzione di alcuni esperimenti.

Fine-grained indoor positioning and tracking systems

Indoor positioning has attracted considerable attention for decades due to the increasing demands for location based services. In the past years, although numerous methods have been proposed for indoor positioning, it is still challenging to find a convincing solution that combines high positioning accuracy and ease of deployment. Radio-based indoor positioning has emerged as a dominant method due to its ubiquitousness, especially for WiFi. RSSI (Received Signal Strength Indicator) has been investigated in the area of indoor positioning for decades. However, it is prone to multipath propagation and hence fingerprinting has become the most commonly used method for indoor positioning using RSSI. The drawback of fingerprinting is that it requires intensive labour efforts to calibrate the radio map prior to experiments, which makes the deployment of the positioning system very time consuming. Using time information as another way for radio-based indoor positioning is challenged by time synchronization among anchor nodes and timestamp accuracy. Besides radio-based positioning methods, intensive research has been conducted to make use of inertial sensors for indoor tracking due to the fast developments of smartphones. However, these methods are normally prone to accumulative errors and might not be available for some applications, such as passive positioning. This thesis focuses on network-based indoor positioning and tracking systems, mainly for passive positioning, which does not require the participation of targets in the positioning process. To achieve high positioning accuracy, we work on some information of radio signals from physical-layer processing, such as timestamps and channel information. The contributions in this thesis can be divided into two parts: time-based positioning and channel information based positioning. First, for time-based indoor positioning (especially for narrow-band signals), we address challenges for compensating synchronization offsets among anchor nodes, designing timestamps with high resolution, and developing accurate positioning methods. Second, we work on range-based positioning methods with channel information to passively locate and track WiFi targets. Targeting less efforts for deployment, we work on range-based methods, which require much less calibration efforts than fingerprinting. By designing some novel enhanced methods for both ranging and positioning (including trilateration for stationary targets and particle filter for mobile targets), we are able to locate WiFi targets with high accuracy solely relying on radio signals and our proposed enhanced particle filter significantly outperforms the other commonly used range-based positioning algorithms, e.g., a traditional particle filter, extended Kalman filter and trilateration algorithms. In addition to using radio signals for passive positioning, we propose a second enhanced particle filter for active positioning to fuse inertial sensor and channel information to track indoor targets, which achieves higher tracking accuracy than tracking methods solely relying on either radio signals or inertial sensors.

Distributed collaborative processing in wireless sensor networks with application to target localization and beamforming

Abstract The proliferation of wireless sensor networks and the variety of envisioned applications associated with them has motivated the development of distributed algorithms for collaborative processing over networked systems. One of the applications that has attracted the attention of the researchers is that of target localization where the nodes of the network try to estimate the position of an unknown target that lies within its coverage area. Particularly challenging is the problem of estimating the target’s position when we use received signal strength indicator (RSSI) due to the nonlinear relationship between the measured signal and the true position of the target. Many of the existing approaches suffer either from high computational complexity (e.g., particle filters) or lack of accuracy. Further, many of the proposed solutions are centralized which make their application to a sensor network questionable. Depending on the application at hand and, from a practical perspective it could be convenient to find a balance between localization accuracy and complexity. Into this direction we approach the maximum likelihood location estimation problem by solving a suboptimal (and more tractable) problem. One of the main advantages of the proposed scheme is that it allows for a decentralized implementation using distributed processing tools (e.g., consensus and convex optimization) and therefore, it is very suitable to be implemented in real sensor networks. If further accuracy is needed an additional refinement step could be performed around the found solution. Under the assumption of independent noise among the nodes such local search can be done in a fully distributed way using a distributed version of the Gauss-Newton method based on consensus. Regardless of the underlying application or function of the sensor network it is al¬ways necessary to have a mechanism for data reporting. While some approaches use a special kind of nodes (called sink nodes) for data harvesting and forwarding to the outside world, there are however some scenarios where such an approach is impractical or even impossible to deploy. Further, such sink nodes become a bottleneck in terms of traffic flow and power consumption. To overcome these issues instead of using sink nodes for data reporting one could use collaborative beamforming techniques to forward directly the generated data to a base station or gateway to the outside world. In a dis-tributed environment like a sensor network nodes cooperate in order to form a virtual antenna array that can exploit the benefits of multi-antenna communications. In col-laborative beamforming nodes synchronize their phases in order to add constructively at the receiver. Some of the inconveniences associated with collaborative beamforming techniques is that there is no control over the radiation pattern since it is treated as a random quantity. This may cause interference to other coexisting systems and fast bat-tery depletion at the nodes. Since energy-efficiency is a major design issue we consider the development of a distributed collaborative beamforming scheme that maximizes the network lifetime while meeting some quality of service (QoS) requirement at the re¬ceiver side. Using local information about battery status and channel conditions we find distributed algorithms that converge to the optimal centralized beamformer. While in the first part we consider only battery depletion due to communications beamforming, we extend the model to account for more realistic scenarios by the introduction of an additional random energy consumption. It is shown how the new problem generalizes the original one and under which conditions it is easily solvable. By formulating the problem under the energy-efficiency perspective the network’s lifetime is significantly improved. Resumen La proliferación de las redes inalámbricas de sensores junto con la gran variedad de posi¬bles aplicaciones relacionadas, han motivado el desarrollo de herramientas y algoritmos necesarios para el procesado cooperativo en sistemas distribuidos. Una de las aplicaciones que suscitado mayor interés entre la comunidad científica es la de localization, donde el conjunto de nodos de la red intenta estimar la posición de un blanco localizado dentro de su área de cobertura. El problema de la localization es especialmente desafiante cuando se usan niveles de energía de la seal recibida (RSSI por sus siglas en inglés) como medida para la localization. El principal inconveniente reside en el hecho que el nivel de señal recibida no sigue una relación lineal con la posición del blanco. Muchas de las soluciones actuales al problema de localization usando RSSI se basan en complejos esquemas centralizados como filtros de partículas, mientas que en otras se basan en esquemas mucho más simples pero con menor precisión. Además, en muchos casos las estrategias son centralizadas lo que resulta poco prácticos para su implementación en redes de sensores. Desde un punto de vista práctico y de implementation, es conveniente, para ciertos escenarios y aplicaciones, el desarrollo de alternativas que ofrezcan un compromiso entre complejidad y precisión. En esta línea, en lugar de abordar directamente el problema de la estimación de la posición del blanco bajo el criterio de máxima verosimilitud, proponemos usar una formulación subóptima del problema más manejable analíticamente y que ofrece la ventaja de permitir en¬contrar la solución al problema de localization de una forma totalmente distribuida, convirtiéndola así en una solución atractiva dentro del contexto de redes inalámbricas de sensores. Para ello, se usan herramientas de procesado distribuido como los algorit¬mos de consenso y de optimización convexa en sistemas distribuidos. Para aplicaciones donde se requiera de un mayor grado de precisión se propone una estrategia que con¬siste en la optimización local de la función de verosimilitud entorno a la estimación inicialmente obtenida. Esta optimización se puede realizar de forma descentralizada usando una versión basada en consenso del método de Gauss-Newton siempre y cuando asumamos independencia de los ruidos de medida en los diferentes nodos. Independientemente de la aplicación subyacente de la red de sensores, es necesario tener un mecanismo que permita recopilar los datos provenientes de la red de sensores. Una forma de hacerlo es mediante el uso de uno o varios nodos especiales, llamados nodos “sumidero”, (sink en inglés) que actúen como centros recolectores de información y que estarán equipados con hardware adicional que les permita la interacción con el exterior de la red. La principal desventaja de esta estrategia es que dichos nodos se convierten en cuellos de botella en cuanto a tráfico y capacidad de cálculo. Como alter¬nativa se pueden usar técnicas cooperativas de conformación de haz (beamforming en inglés) de manera que el conjunto de la red puede verse como un único sistema virtual de múltiples antenas y, por tanto, que exploten los beneficios que ofrecen las comu¬nicaciones con múltiples antenas. Para ello, los distintos nodos de la red sincronizan sus transmisiones de manera que se produce una interferencia constructiva en el recep¬tor. No obstante, las actuales técnicas se basan en resultados promedios y asintóticos, cuando el número de nodos es muy grande. Para una configuración específica se pierde el control sobre el diagrama de radiación causando posibles interferencias sobre sis¬temas coexistentes o gastando más potencia de la requerida. La eficiencia energética es una cuestión capital en las redes inalámbricas de sensores ya que los nodos están equipados con baterías. Es por tanto muy importante preservar la batería evitando cambios innecesarios y el consecuente aumento de costes. Bajo estas consideraciones, se propone un esquema de conformación de haz que maximice el tiempo de vida útil de la red, entendiendo como tal el máximo tiempo que la red puede estar operativa garantizando unos requisitos de calidad de servicio (QoS por sus siglas en inglés) que permitan una decodificación fiable de la señal recibida en la estación base. Se proponen además algoritmos distribuidos que convergen a la solución centralizada. Inicialmente se considera que la única causa de consumo energético se debe a las comunicaciones con la estación base. Este modelo de consumo energético es modificado para tener en cuenta otras formas de consumo de energía derivadas de procesos inherentes al funcionamiento de la red como la adquisición y procesado de datos, las comunicaciones locales entre nodos, etc. Dicho consumo adicional de energía se modela como una variable aleatoria en cada nodo. Se cambia por tanto, a un escenario probabilístico que generaliza el caso determinista y se proporcionan condiciones bajo las cuales el problema se puede resolver de forma eficiente. Se demuestra que el tiempo de vida de la red mejora de forma significativa usando el criterio propuesto de eficiencia energética.

Multi-agent location system in wireless networks

In this paper we propose a flexible Multi-Agent Architecture together with a methodology for indoor location which allows us to locate any mobile station (MS) such as a Laptop, Smartphone, Tablet or a robotic system in an indoor environment using wireless technology. Our technology is complementary to the GPS location finder as it allows us to locate a mobile system in a specific room on a specific floor using the Wi-Fi networks. The idea is that any MS will have an agent known at a Fuzzy Location Software Agent (FLSA) with a minimum capacity processing at its disposal which collects the power received at different Access Points distributed around the floor and establish its location on a plan of the floor of the building. In order to do so it will have to communicate with the Fuzzy Location Manager Software Agent (FLMSA). The FLMSAs are local agents that form part of the management infrastructure of the Wi-Fi network of the Organization. The FLMSA implements a location estimation methodology divided into three phases (measurement, calibration and estimation) for locating mobile stations (MS). Our solution is a fingerprint-based positioning system that overcomes the problem of the relative effect of doors and walls on signal strength and is independent of the network device manufacturer. In the measurement phase, our system collects received signal strength indicator (RSSI) measurements from multiple access points. In the calibration phase, our system uses these measurements in a normalization process to create a radio map, a database of RSS patterns. Unlike traditional radio map-based methods, our methodology normalizes RSS measurements collected at different locations on a floor. In the third phase, we use Fuzzy Controllers to locate an MS on the plan of the floor of a building. Experimental results demonstrate the accuracy of the proposed method. From these results it is clear that the system is highly likely to be able to locate an MS in a room or adjacent room.