Wireless underground sensor networks enable many applications, such as mine and tunnel disaster prevention, oil upstream monitoring, earthquake prediction and landslide detection, and intelligent farming and irrigatio...
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Wireless underground sensor networks enable many applications, such as mine and tunnel disaster prevention, oil upstream monitoring, earthquake prediction and landslide detection, and intelligent farming and irrigation among many others. Most applications are location-dependent, so they require precise sensor positions. However, classical localization solutions based on the propagation properties of electromagnetic waves do not function well in underground environments. This paper proposes a magnetic induction (MI)-based localization that accurately and efficiently locates randomly deployed sensors in underground environments by leveraging the multipath fading free nature of MI signals. Specifically, the MI-based localization framework is first proposed based on underground MI channel modeling with additive white Gaussian noise, the designated error function, and semidefinite programming relaxation. Next, this paper proposes a two-step positioning mechanism for obtaining fast and accurate localization results by: first, developing the fast-initial positioning through an alternating direction augmented Lagrangian method for rough sensor locations within a short processing time, and then proposing fine-grained positioning for performing powerful search for optimal location estimations via the conjugate gradient algorithm. Simulations confirm that our solution yields accurate sensor locations with both low and high noise and reveals the fundamental impact of underground environments on the localization performance.
The localization of nodes plays a fundamental role in Wireless Sensor and Actors Networks (WSAN) identifying geographically where an event occurred, which facilitates timely response to this action. This article prese...
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The localization of nodes plays a fundamental role in Wireless Sensor and Actors Networks (WSAN) identifying geographically where an event occurred, which facilitates timely response to this action. This article presents a performance evaluation of multi-hop localization range-free algorithms used in WSAN, such as Distance Vector Hop (DV-Hop), Improved DV-Hop (IDV-Hop), and the Weighted DV-Hop (WDV-Hop). In addition, we propose a new localization algorithm, merging WDV-Hop, with the weighted hyperbolic localization algorithm (WH), which includes weights to the correlation matrix of the estimated distances between the node of interest (NOI) and the reference nodes (RN) in order to improve accuracy and precision. As performance metrics, the accuracy, precision, and computational complexity are evaluated. The algorithms are evaluated in three scenarios where all nodes are randomly distributed in a given area, varying the number of RNs, the density of nodes in the network, and radio coverage of the nodes. The results show that in networks with 100 nodes, WDV-Hop outperforms the DV-Hop and IDV-Hop even if the number of RNs is reduced to 10. Moreover, our proposal shows an improvement in terms of accuracy and precision at the cost of increased computational complexity, specifically in the algorithm execution time, but without affecting the hardware cost or power consumption.
Accurate locating for the mobile target remains a challenge in various applications of wireless sensor networks (WSNs). Unfortunately, most of the typical localization algorithms perform well only in the WSN with dens...
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Accurate locating for the mobile target remains a challenge in various applications of wireless sensor networks (WSNs). Unfortunately, most of the typical localization algorithms perform well only in the WSN with densely distributed sensor nodes. The non-localizable problem is prone to happening when a target moves into the WSN with sparsely distributed sensor nodes. To solve this problem, we propose a collaborative and predictive localization algorithm (CPLA). The Gaussian mixture model (GMM) is introduced to predict the posterior trajectory for a mobile target by training its prior trajectory. In addition, the collaborative and predictive schemes are designed to solve the non-localizable problems in the two-anchor nodes locating, one-anchor node locating and non-anchor node locating situations. Simulation results prove that the CPLA exhibits higher localization accuracy than other tested predictive localization algorithms either in the WSN with sparsely distributed sensor nodes or in the WSN with densely distributed sensor nodes.
The growing number of mobile devices and the popularity of Internet of Things (IoT) applications have caused an increase of local-area location-aware protocols and applications. localization has become a popular topic...
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ISBN:
(数字)9783319597676
ISBN:
(纸本)9783319597676
The growing number of mobile devices and the popularity of Internet of Things (IoT) applications have caused an increase of local-area location-aware protocols and applications. localization has become a popular topic in the literature and many localization algorithms in wireless sensor networks (WSN) have been proposed. However, the most of them are vulnerable to common wireless attacks. In this article, we introduce the secure localization protocol based on a RSSI-mapping, which uses symmetric cryptography. The security attributes of the protocol have been proved using the Scyther tool. We present the experimental results that demonstrate the ability to estimate sensor's location in the environment, where other networks are available. The results show, that the introduction of security mechanisms to localization protocols may significantly increase the execution time and exceed strict time restrictions in some real-time applications. Nevertheless, the existence of insecure protocol in hostile environment is unacceptable. To achieve a better efficiency, we suggest to use the hardware encryption provided in CC2420 radio chip.
Sensor localization is demanded by wireless sensor networks, since the collected sensor data are meaningless if the position of the generating sensor is not available. The traditional approach of using GPS for locatio...
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Sensor localization is demanded by wireless sensor networks, since the collected sensor data are meaningless if the position of the generating sensor is not available. The traditional approach of using GPS for location determination is not suitable for sensor networks, due to the increased costs and resource usage. For this reason, sensors exchange Radio Frequency messages, so as to measure their respective distances and determine their locations by means of multilateral triangulation with sensors of known positions, called anchors. Such an approach, however, is particularly vulnerable to several kinds of attacks aiming at causing wrong position estimations with a malicious intention. Such attacks can be tolerated with proper countermeasures, belonging to the so called secure localization, but this is achieved at the expenses of high costs in terms of exchanged messages and exhausted sensor resources, such as the battery. For these reasons, it is crucial to use the secure localization only when needed in order to extend considerably the life span of the sensors. Therefore, we propose to model the interaction of an anchor with a sensor as a signaling game, and to use such a formalization to discipline the use of secure positioning methods based on the received messages from the anchors. We have proved with simulations that such a solution is more efficient than a naive one of always applying secure localization. (C) 2017 Elsevier B.V. All rights reserved.
Direction of arrival (DoA) estimation in the massive antenna systems with reduced hardware and signal processing complexity is a challenging task. To address the issue, this paper presents an approach to estimate the ...
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ISBN:
(纸本)9781538621011
Direction of arrival (DoA) estimation in the massive antenna systems with reduced hardware and signal processing complexity is a challenging task. To address the issue, this paper presents an approach to estimate the DoA in a large number of antennas system combined with an electromagnetic (EM) lens. An EM lens has the ability to focus the received signal energy as a function of the angle of arrival (AoA) to a small subset/area of the antenna array at the base station (BS). Thus, it helps to estimate the DoA efficiently while minimizing the number of radio frequency (RF) chains and the associated signal processing costs. Moreover, by defining a cluster over a group of closely spaced subsets, the computational efforts of the DoA estimation algorithm can be further reduced.
Position estimation is a crucial aspect of localization in Wireless Sensor Networks (WSNs) as estimated sensor location is used in many applications of WSNs. Various localization algorithms have been developed over th...
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Position estimation is a crucial aspect of localization in Wireless Sensor Networks (WSNs) as estimated sensor location is used in many applications of WSNs. Various localization algorithms have been developed over the time for obtaining the highest precision in location estimation. The main idea in most of the popular algorithms is to estimate the position of sensors with help of some special beacon nodes with known coordinates. Favorable method that provides a better accuracy with lowest network cost is to replace all special beacons with a single beacon equipped with GPS unit. In this case, the fundamental problem is to design a trajectory that the mobile beacon should follow which minimizes the localization error. In this paper, we provide an up-to-date state-of-the-art of the most important anchor node trajectories designed to localize static sensors. We have evaluated the performance of the existing schemes through a series of simulations in MATLAB. Furthermore, we highlight some issues experienced by these techniques.
In this paper, we develop a novel optimal anchors placement strategy tailored for anisotropic WSNs. By resorting to the well-known particle swarm optimization (PSO), we derive the optimal anchors' positions that m...
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ISBN:
(纸本)9781509003044
In this paper, we develop a novel optimal anchors placement strategy tailored for anisotropic WSNs. By resorting to the well-known particle swarm optimization (PSO), we derive the optimal anchors' positions that minimize the average location estimation error (LEE). We show that our placement strategy provides substantial accuracy gains if used instead of the conventional ones and that it is able to reduce not only the average LEE but also the LEE itself and, hence, guarantees high accuracy for any WSN configuration.
On 18 November 2014, a team of four autonomous CoBot robots reached 1,000-km of overall autonomous navigation, as a result of a 1,000-km challenge that the authors had set three years earlier. The authors are frequent...
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On 18 November 2014, a team of four autonomous CoBot robots reached 1,000-km of overall autonomous navigation, as a result of a 1,000-km challenge that the authors had set three years earlier. The authors are frequently asked for the lessons learned, as well as the performance results. In this article, they introduce the challenge and contribute a detailed presentation of technical insights as well as quantitative and qualitative results. They have previously presented the algorithms for the individual technical contributions, namely robot localization, symbiotic robot autonomy, and robot task scheduling. In this article, they present the data collected over the 1,000-km challenge and analyze it to evaluate the accuracy and robustness of the localization algorithms on the CoBots. Furthermore, they present technical insights into the algorithms, which they believe are responsible for the robots" continuous robust performance.
An accurate localization algorithm tailored for anisotropic wireless sensors networks (WSN)s is proposed in this paper. Using the proposed algorithm, each regular or position-unaware node estimates its distances only ...
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ISBN:
(纸本)9781467365550
An accurate localization algorithm tailored for anisotropic wireless sensors networks (WSN)s is proposed in this paper. Using the proposed algorithm, each regular or position-unaware node estimates its distances only to reliable anchors or position-aware nodes. The latter are properly chosen following a new reliable anchor selection strategy that ensures an accurate distance estimation making thereby our localization algorithm more precise. Simulations show that our algorithm, consistently outperforms the best representative localization algorithms currently available in the literature in terms of accuracy, even with the presence of non-uniform node distribution or radiation irregularities.
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