Node Localization In Wireless Sensor Networks
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Node Localization In Wireless Sensor Networks
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Author : Xue Zhang
language : en
Publisher: Springer
Release Date : 2016-12-18
Node Localization In Wireless Sensor Networks written by Xue Zhang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-18 with Technology & Engineering categories.
In sensor network applications, measured data are often meaningful only when the location is accurately known. In this booklet, we study research problems associated with node localization in wireless sensor networks. We describe sensor network localization problems in terms of a detection and estimation framework and we emphasize specifically a cooperative process where sensors with known locations are used to localize nodes at unknown locations. In this class of problems, even if the location of a node is known, the wireless links and transmission modalities between two nodes may be unknown. In this case, sensor nodes are used to detect the location and estimate pertinent data transmission activities between nodes. In addition to the broader problem of sensor localization, this booklet studies also specific localization measurements such as time of arrival (TOA), received signal strength (RSS), and direction of arrival (DOA). The sequential localization algorithm, which uses a subset of sensor nodes to estimate nearby sensor nodes' locations is discussed in detail. Extensive bibliography is given for those readers who want to delve further into specific topics.
Robust Node Localization For Wireless Sensor Networks
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Author : Radu Stoleru
language : en
Publisher:
Release Date : 2007
Robust Node Localization For Wireless Sensor Networks written by Radu Stoleru and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
Wireless Sensor Network (WSN) systems have been used in many promising applications including military surveillance, habitat monitoring and wildlife tracking. While many middleware services to support these applications have been designed and implemented successfully, node localization - finding the position of a sensor node - remains one of the most difficult research challenges to be solved.
Timing Synchronization And Node Localization In Wireless Sensor Networks
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Author : Aitzaz Ahmad
language : en
Publisher:
Release Date : 2013
Timing Synchronization And Node Localization In Wireless Sensor Networks written by Aitzaz Ahmad and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
Wireless sensor networks (WSNs) consist of a large number of sensor nodes, capable of on-board sensing and data processing, that are employed to observe some phenomenon of interest. With their desirable properties of flexible deployment, resistance to harsh environment and lower implementation cost, WSNs envisage a plethora of applications in diverse areas such as industrial process control, battle- field surveillance, health monitoring, and target localization and tracking. Much of the sensing and communication paradigm in WSNs involves ensuring power efficient transmission and finding scalable algorithms that can deliver the desired performance objectives while minimizing overall energy utilization. Since power is primarily consumed in radio transmissions delivering timing information, clock synchronization represents an indispensable requirement to boost network lifetime. This dissertation focuses on deriving efficient estimators and performance bounds for the clock parameters in a classical frequentist inference approach as well as in a Bayesian estimation framework. A unified approach to the maximum likelihood (ML) estimation of clock offset is presented for different network delay distributions. This constitutes an analytical alternative to prior works which rely on a graphical maximization of the likelihood function. In order to capture the imperfections in node oscillators, which may render a time-varying nature to the clock offset, a novel Bayesian approach to the clock offset estimation is proposed by using factor graphs. Message passing using the max-product algorithm yields an exact expression for the Bayesian inference problem. This extends the current literature to cases where the clock offset is not deterministic, but is in fact a random process. A natural extension of pairwise synchronization is to develop algorithms for the more challenging case of network-wide synchronization. Assuming exponentially distributed random delays, a network-wide clock synchronization algorithm is proposed using a factor graph representation of the network. Message passing using the max- product algorithm is adopted to derive the update rules for the proposed iterative procedure. A closed form solution is obtained for each node's belief about its clock offset at each iteration. Identifying the close connections between the problems of node localization and clock synchronization, we also address in this dissertation the problem of joint estimation of an unknown node's location and clock parameters by incorporating the effect of imperfections in node oscillators. In order to alleviate the computational complexity associated with the optimal maximum a-posteriori estimator, two iterative approaches are proposed as simpler alternatives. The first approach utilizes an Expectation-Maximization (EM) based algorithm which iteratively estimates the clock parameters and the location of the unknown node. The EM algorithm is further simplified by a non-linear processing of the data to obtain a closed form solution of the location estimation problem using the least squares (LS) approach. The performance of the estimation algorithms is benchmarked by deriving the Hybrid Cramer-Rao lower bound (HCRB) on the mean square error (MSE) of the estimators. We also derive theoretical lower bounds on the MSE of an estimator in a classical frequentist inference approach as well as in a Bayesian estimation framework when the likelihood function is an arbitrary member of the exponential family. The lower bounds not only serve to compare various estimators in our work, but can also be useful in their own right in parameter estimation theory. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/148131
Anchor Node Placement For Localization In Wireless Sensor Networks
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Author : Benjamin Leo Tatham
language : en
Publisher:
Release Date : 2011
Anchor Node Placement For Localization In Wireless Sensor Networks written by Benjamin Leo Tatham and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Electrical engineering categories.
Evaluation Of The Received Signal Strength Indicator For Node Localization In Wireless Sensor Networks
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Author : Siarhei Smolau
language : en
Publisher:
Release Date : 2009
Evaluation Of The Received Signal Strength Indicator For Node Localization In Wireless Sensor Networks written by Siarhei Smolau and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
Reducing Delay For The Node Localization Of Wsn
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Author : Independently Published
language : en
Publisher:
Release Date : 2018-10-06
Reducing Delay For The Node Localization Of Wsn written by Independently Published and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-06 with categories.
For collecting information from applications spread across large areas several sensor nodes are deployed and the network generated due to the wireless communication of these nodes is known as wireless sensor network. The data that is collected from surrounding areas is passed on by the sensors to a base station such that further processing can be performed on it. However, the size of a sensor node is very small due to which it includes very less power, memory and also its capacity of perform operations is less. In order to ensure that the complete region is deployed with sensor nodes, random deployment of nodes is done in these networks. This helps in gathering the information from all parts of the region and sending it to the base station.
Evaluation And Analysis Of Node Localization Power Cost In Ad Hoc Wireless Sensor Networks With Mobility
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Author : Brian A. Sessler
language : en
Publisher:
Release Date : 2006
Evaluation And Analysis Of Node Localization Power Cost In Ad Hoc Wireless Sensor Networks With Mobility written by Brian A. Sessler and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Mobile computing categories.
Gradient Descent Localization In Wireless Sensor Networks
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Author : Nuha A.S. Alwan
language : en
Publisher:
Release Date : 2017
Gradient Descent Localization In Wireless Sensor Networks written by Nuha A.S. Alwan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Computers categories.
Meaningful information sharing between the sensors of a wireless sensor network (WSN) necessitates node localization, especially if the information to be shared is the location itself, such as in warehousing and information logistics. Trilateration and multilateration positioning methods can be employed in two-dimensional and three-dimensional space respectively. These methods use distance measurements and analytically estimate the target location; they suffer from decreased accuracy and computational complexity especially in the three-dimensional case. Iterative optimization methods, such as gradient descent (GD), offer an attractive alternative and enable moving target tracking as well. This chapter focuses on positioning in three dimensions using time-of-arrival (TOA) distance measurements between the target and a number of anchor nodes. For centralized localization, a GD-based algorithm is presented for localization of moving sensors in a WSN. Our proposed algorithm is based on systematically replacing anchor nodes to avoid local minima positions which result from the moving target deviating from the convex hull of the anchors. We also propose a GD-based distributed algorithm to localize a fixed target by allowing gossip between anchor nodes. Promising results are obtained in the presence of noise and link failures compared to centralized localization. Convergence factor issues are discussed, and future work is outlined.
Secure Localization And Time Synchronization For Wireless Sensor And Ad Hoc Networks
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Author : Radha Poovendran
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-03
Secure Localization And Time Synchronization For Wireless Sensor And Ad Hoc Networks written by Radha Poovendran and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-03 with Technology & Engineering categories.
Localization is a critical process in mobile ad hoc networks and wireless sensor networks. Wireless sensor node or MANET devices need to know the network's location or its relative location, with respect to the rest of the network neighbors. However, due to the open spectrum nature of wireless communication, it is subject to attacks and intrusions. Hence the wireless network synchronization needs to be both robust and secure. Furthermore, issues such as energy constraints and mobility make the localization process even more challenging. Secure Localization and Time Synchronization for Wireless Sensor and Ad Hoc Networks presents the latest research results in the area of secure localization for both wireless mobile ad hoc networks and wireless sensor networks.
Icca Map
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Author : Shafagh Alikhani
language : en
Publisher:
Release Date : 2010
Icca Map written by Shafagh Alikhani and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computer science categories.