245 research outputs found
A survey of localization in wireless sensor network
Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network
Radio Communications
In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modiďŹed our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the ďŹeld of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks
Optimization of positioning capabilities in wireless sensor networks : from power efficiency to medium access
In Wireless Sensor Networks (WSN), the ability of sensor nodes to know its position is an enabler for a wide variety of applications for monitoring, control, and automation. Often, sensor data is meaningful only if its position can be determined. Many WSN are deployed indoors or in areas where Global Navigation Satellite System (GNSS) signal coverage is not available, and thus GNSS positioning cannot be guaranteed. In these scenarios, WSN may be relied upon to achieve a satisfactory degree of positioning accuracy. Typically, batteries power sensor nodes in WSN. These batteries are costly to replace. Therefore, power consumption is an important aspect, being performance and lifetime of WSN strongly relying on the ability to reduce it. It is crucial to design effective strategies to maximize battery lifetime. Optimization of power consumption can be made at different layers. For example, at the physical layer, power control and resource optimization may play an important role, as well as at higher layers through network topology and MAC protocols.
The objective of this Thesis is to study the optimization of resources in WSN that are employed for positioning purposes, with the ultimate goal being the minimization of power consumption. We focus on anchor-based positioning, where a subset of the WSN nodes know their location (anchors) and send ranging signals to nodes with unknown position (targets) to assist them in estimating it through distance-related measurements. Two well known of such measurements are received signal strength (RSS) and time of arrival (TOA), in which this Thesis focuses. In order to minimize power consumption while providing a certain quality of positioning service, in this dissertation we research on the problems of power control and node selection. Aiming at a distributed implementation of the proposed techniques, we resort to the tools of non-cooperative game theory.
First, transmit power allocation is addressed for RSS based ranging. Using game theory formulation, we develop a potential game leading to an iterated best response algorithm with sure convergence. As a performance metric, we introduce the geometric dilution of precision (GDOP), which is shown to help achieving a suitable geometry of the selected anchor nodes. The proposed scheme and relative distributed algorithms provide good equilibrium performance in both static and dynamic scenarios. Moreover, we present a distributed, low complexity implementation and analyze it in terms of computational complexity. Results show that performance close to that of exhaustive search is possible.
We then address the transmit power allocation problem for TOA based ranging, also resorting to a game theoretic formulation. In this setup, and also considering GDOP as performance metric, a supermodular game formulation is proposed, along with a distributed algorithm with guaranteed convergence to a unique solution, based on iterated best response. We analyze the proposed algorithm in terms of the price of anarchy (PoA), that is, compared to a centralized optimum solution, and shown to have a moderate performance loss.
Finally, this dissertation addresses the effect of different MAC protocols and topologies in the positioning performance. In this direction, we study the performance of mesh and cluster-tree topologies defined in WSN standards. Different topologies place different constraints in network connectivity, having a substantial impact on the performance of positioning algorithms. While mesh topology allows high connectivity with large energy consumption, cluster-tree topologies are more energy efficient but suffer from reduced connectivity and poor positioning performance. In order to improve the performance of cluster-tree topologies, we propose a cluster formation algorithm. It significantly improves connectivity with anchor nodes, achieving vastly improved positioning performance.En les xarxes de sensors sense fils (WSN), l'habilitat dels nodes sensors per conèixer la seva posiciĂł facilita una gran varietat d'aplicacions per la monitoritzaciĂł, el control i l'automatitzaciĂł. AixĂ, les dades que proporciona un sensor tenen sentit nomĂŠs si la posiciĂł pot ĂŠsser determinada. Moltes WSN sĂłn desplegades en interiors o en Ă rees on la senyal de sistemes globals de navegaciĂł per satèl.lit (GNSS) no tĂŠ prou cobertura, i per tant, el posicionament basat en GNSS no pot ĂŠsser garantitzat. En aquests escenaris, les WSN poden proporcionar una bona precisiĂł en posicionament. Normalment, en WSN els nodes sĂłn alimentats amb bateries. Aquestes bateries sĂłn difĂcils de reemplaçar. Per tant, el consum de potència ĂŠs un aspecte important i ĂŠs crucial dissenyar estratègies efectives per maximitzar el temps de vida de la bateria. L'optimitzaciĂł del consum de potència pot ser fet a diferents capes del protocol. Per exemple, en la capa fĂsica, el control de potència i l'optimitzaciĂł dels recursos juguen un rol important, igualment que la topologia de xarxa i els protocols MAC en les capes mĂŠs altes. L'objectiu d'aquesta tesi ĂŠs estudiar lÂżoptimitzaciĂł de recursos en WSN que s'utilitzen per fer posicionament, amb el propòsit de minimitzar el consum de potència. Ens focalitzem en el posicionament basat en Ă ncora, en el qual un conjunt de nodes coneixen la seva localitzaciĂł (nodes Ă ncora) i envien missatges als nodes que no saben la seva posiciĂł per ajudar-los a estimar les seves coordenades amb mesures de distĂ ncia. Dues classes de mesures sĂłn la potència de la senyal rebuda (RSS) i el temps d'arribada (TOA) en les quals aquesta tesi estĂ focalitzada. Per minimitzar el consum de potència mentre que es proporciona suficient qualitat en el posicionament, en aquesta tesi estudiem els problemes de control de potència i selecciĂł de nodes. Tenint en compte una implementaciĂł distribuĂŻda de les tècniques proposades, utilitzem eĂŻnes de teoria de jocs no cooperatius. Primer, l'assignaciĂł de potència transmesa ĂŠs abordada pel cĂ lcul de la distĂ ncia amb RSS. Utilitzant la teoria de jocs, desenvolupem un joc potencial que convergeix amb un algoritme iteratiu basat en millor resposta (best response). Com a mètrica d'error, introduĂŻm la diluciĂł de la precisiĂł geomètrica (GDOP) que mostra quant d'apropiada ĂŠs la geometria dels nodes Ă ncora seleccionats. L'esquema proposat i els algoritmes distribuĂŻts proporcionen una bona resoluciĂł de l'equilibri en l'escenari estĂ tic i dinĂ mic. Altrament, presentem una implementaciĂł distribuĂŻda i analitzem la seva complexitat computacional. Els resultats obtinguts sĂłn similars als obtinguts amb un algoritme de cerca exhaustiva. El problema d'assignaciĂł de la potència transmesa en el cĂ lcul de la distĂ ncia basat en TOA, tambĂŠ ĂŠs tractat amb teoria de jocs. En aquest cas, considerant el GDOP com a mètrica d'error, proposem un joc supermodular juntament amb un algoritme distribuĂŻt basat en millor resposta amb convergència garantida cap a una Ăşnica soluciĂł. Analitzem la soluciĂł proposada amb el preu de l'anarquia (PoA), ĂŠs a dir, es compara la nostra soluciĂł amb una soluciĂł òptima centralitzada mostrant que les pèrdues sĂłn moderades. Finalment, aquesta tesi tracta l'efecte que causen diferents protocols MAC i topologies en el posicionament. En aquesta direcciĂł, estudiem les topologies de malla i arbre formant clusters (cluster-tree) que estan definides als estĂ ndards de les WSN. La diferència entre les topologies crea diferents restriccions en la connectivitat de la xarxa, afectant els resultats de posicionament. La topologia de malla permet una elevada connectivitat entre els nodes amb gran consum d'energia, mentre que les topologies d'arbre sĂłn mĂŠs energèticament eficients però amb baixa connectivitat entre els nodes i baix rendiment pel posicionament. Per millorar la qualitat del posicionament en les topologies d'arbre, proposem un algoritme de formaciĂł de clĂşsters.Postprint (published version
Improving RSSI based distance estimation for wireless sensor networks
In modern everyday life we see gradually increasing number of wireless sensor devices. In some cases it is necessary to know the accurate location of the devices. Most of the usual techniques developed to get this information require a lot of resources (power, bandwidth, computation, extra hardware) which small embedded devices cannot afford. Therefore techniques, using small resources without the need for extra hardware, need to be developed. Wireless sensor networks are often used inside buildings. In such environment satellite positioning is not available. As a consequence, the location computation must be done in network-based manner.
In this thesis a received signal strength indicator (RSSI) based distance estimation technique for 802.15.4 network based on CC2431 radio is discussed. In this approach we try to differentiate between good and erroneous measurements by imposing limits based on standard deviation of RSSI and the number of lost packets. These limits are included as a part of the model parameter estimation process. These limits are optimized in order to improve the resulting distance estimates with minimum loss of connectivity information. We experimentally evaluated the merits of the proposed method and found it to be useful under certain circumstances.fi=OpinnäytetyÜ kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format
Localisation in wireless sensor networks for disaster recovery and rescuing in built environments
A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyProgress in micro-electromechanical systems (MEMS) and radio frequency (RF) technology has fostered the development of wireless sensor networks (WSNs). Different from traditional networks, WSNs are data-centric, self-configuring and self-healing. Although WSNs have been successfully applied in built environments (e.g. security and services in smart homes), their applications and benefits have not been fully explored in areas such as disaster recovery and rescuing. There are issues related to self-localisation as well as practical constraints to be taken into account.
The current state-of-the art communication technologies used in disaster scenarios are challenged by various limitations (e.g. the uncertainty of RSS). Localisation in WSNs (location sensing) is a challenging problem, especially in disaster environments and there is a need for technological developments in order to cater to disaster conditions. This research seeks to design and develop novel localisation algorithms using WSNs to overcome the limitations in existing techniques. A novel probabilistic fuzzy logic based range-free localisation algorithm (PFRL) is devised to solve localisation problems for WSNs. Simulation results show that the proposed algorithm performs better than other range free localisation algorithms (namely DVhop localisation, Centroid localisation and Amorphous localisation) in terms of localisation accuracy by 15-30% with various numbers of anchors and degrees of radio propagation irregularity.
In disaster scenarios, for example, if WSNs are applied to sense fire hazards in building, wireless sensor nodes will be equipped on different floors. To this end, PFRL has been extended to solve sensor localisation problems in 3D space. Computational results show that the 3D localisation algorithm provides better localisation accuracy when varying the system parameters with different communication/deployment models. PFRL is further developed by applying dynamic distance measurement updates among the moving sensors in a disaster environment. Simulation results indicate that the new method scales very well
Energy-efficient mobile node localization using CVA technology and SAI algorithm
In the evolving landscape of the Internet of Things (IoT), Mobile Wireless Sensor Networks (MWSN) play a pivotal role, particularly in dynamic environments requiring mobile sensing capabilities. A primary challenge in MWSNs is achieving accurate node positioning with minimal energy consumption, as these networks often consist of battery-powered, mobile sensors where energy replenishment is difficult. This paper addresses the critical problem of energy-efficient node localization in MWSNs. We propose a novel positioning approach leveraging Cooperative Virtual Array (CVA) technology, which strategically utilizes the mobility of nodes to enhance positioning accuracy while conservatively using energy resources. The methodology revolves around optimizing the number of transceiver nodes, considering factors such as node moving speed, total energy consumption, and positioning errors. Central to our approach is the Signal Arrival and Interaction (SAI) algorithm, an innovative technique devised for efficient and precise mobile node localization, replacing traditional Time of Arrival (ToA) methods. Our simulations, conducted under various scenarios, demonstrate the significant advantages of the CVA-based positioning algorithm. Results show a marked reduction in energy consumption and robust performance in mobile node scenarios. Key findings include substantial improvements in localization accuracy and energy efficiency, highlighting the potential of our approach in enhancing the operational sustainability of MWSNs. The implications of this research are far-reaching for IoT applications, particularly those involving mobile sensors, such as in smart cities, industrial monitoring, and disaster management. By introducing a novel, energy-efficient positioning method, our work contributes to the advancement of MWSN technology, offering a sustainable solution to the challenge of mobile node localization
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