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Identifying and detecting the unknown abnormal sparse signal has become an important issue for distributed networks. In this paper, we proposed a new detection scheme based on convex optimization for wireless sensor networks. Under the Neyman-Pearson testing framework, the detection scheme first estimates the unknown signal by employing the convex optimization at the fusion center. Then the sensor...
Recently, a class of online blind extraction algorithms in the framework of Kalman filtering have been developed for wireless sensor networks applications. But their performance is poor when additive noise is not neglectable. To address this issue, a new blind extraction method is proposed. This method novelly adopts two unscented Kalman filters alternately estimate the extraction vector and the source...
Wireless Sensor Networks are dynamic in nature and the sensor nodes are self-organized. Due to the characteristics of the WSN and its nodes, knowing the location of the nodes is an important factor to be considered to improve the security in WSN. In this paper the location of a node [P] can be obtained using the Nearest Neighbor Reference Method [NNRM] and the reference node is the answer for the...
Wireless Sensor Networks (WSNs) have been of high interest during the past couple of years. One of the most important aspects of WSN research is location estimation. As a good solution of fine grained localization Reichenbach et al. introduced the Distributed Least Squares (DLS) algorithm, which splits the costly localization process in a complex precalculation and a simple postcalculation which is...
A lot of research has been done in finding range-based methods such as computing RSSI, time of arrival, angle of arrival or time difference of arrival and range-free methods such as centroid computation, DV-hop and approximate position in triangle, for localization in wireless sensor networks. Range-based methods estimate location more precisely than range-free methods. However, range-free methods...
We consider problems where multiple agents cooperate to control their individual state so as to optimize a common objective while communicating with each other to exchange state information. Since communication costs can be significant, we seek conditions under which communication of state information among nodes can be minimized while still ensuring that the optimization process converges. In prior...
Wireless sensor networks (WSNs) have been of high interest during the past couple of years. One of the most important aspects of WSN research is location estimation. As a good solution of fine grained localization Reichenbach et al. introduced the distributed least squares (DLS) algorithm, which splits the costly localization process in a complex precalculation and a simple postcalculation which is...
In this paper we propose a technique to determine the decision thresholds in multi-bit distributed detection. Detection thresholds are required to quantize the acquired information from the environment to send them to a fusion center. In multi-bit detection, decision making is complicated and in most cases, methods based on simulation or Person by Person Optimizations are applied to find the thresholds...
Localization is an important research issue in Wireless Sensor Networks (WSNs). Recently, hop-count-based localization has been proposed as a cost-effective alternative to range-based localization algorithms. Traditionally, hop-counts between any pair of nodes can only take on integer values regardless of relative positions of nodes in the hop. We show that by partitioning a node's one-hop neighbor...
Most monitoring or tracking applications require the localization information in wireless sensor network. The DV-Hop provides a basic scheme to retrieve the localization without GPS information. DV-Hop scheme only uses the localizations of the reference nodes and the hop-count, so the fundamental estimation may cause the larger error than range-based schemes. The proposed scheme uses the neighbor...
This paper considers statistical issues of source localization from received signal strength (RSS) measurements affected by log-normal shadowing with focus on bias and variance. We characterize the class of all unbiased estimates of the source position and show that their error variances grow exponentially with the noise power. Finally, we propose an estimate the bias and error variance of which are...
The inherent properties of wireless sensor networks (WSN) disqualify most classic methods targeting timeliness guarantees. Assumptions of such methods as well as a restrictive notion of timeliness borrowed from classic real-time systems clash with the indeterminism of realistic scenarios. In this paper, we introduce a generalized notion of timeliness which allows to provide meaningful performance...
Localization is an essential problem in wireless sensor networks (WSNs). Many localization algorithms have been proposed, but few efforts have been paid on theoretical analysis on the accuracy of these algorithms. Because it is naturally to formalize range-based localization problems as deterministic parameter estimation problems, for range-based localization algorithms Crameacuter-Rao lower bound...
Localization is an important area in wireless sensor networks. In this paper we introduce an efficient distributed location discovery algorithm which is named Distance Control Refinement (DCR). The DCR algorithm improves upon the previous Hop-TERRAIN algorithm by using the last iteration result as current result in some cases. Simulation results show that the fraction of located sensors by using our...
One of the most important aspects of a WSN is its localization scheme. Adequate accuracy, complexity, timing, and vulnerability to environment pitfalls are all worth considering parameters. Here, we propose discrete probabilistic DV-Hop, an enhancement to DV-Hop, a well-known range-free WSN localization algorithm, aiming to improve both its localization accuracy and complexity. One should note that...
Distance measurement between nodes in wireless sensor networks is a prerequisite for a variety of applications and algorithms. However, special hardware allowing such measurements is expensive, especially if dealing with hundreds or thousands of nodes. Fekete et al. presented an approach on distance estimation based on only the neighborhood information available to all nodes in the network. We improve...
As wireless sensor networks are ubiquitous in nature, localization is an important factor to be solved. Localization of an unknown node can be identified through a set of reference nodes. In this paper, we present a novel hybrid localization technique, which determines the exact location coordinates of an unknown node through the combination of both range free and range based methods. The location...
In many applications of Wireless Sensor Networks (WSN), it is crucial to know the location of sensor nodes. Although several methods have been proposed, most of them have poor performance in irregularly shaped networks. MDS-MAP is one of the localization methods based on multidimensional scaling (MDS) technique. It uses the connectivity information to derive the location of the nodes in the network...
Wireless sensor networks had a big diffusion in the last few decades and they are used in many application domains. Services built on them require to handle a big amount of data, and a fundamental requirement is their quality, highly affected by the security of the whole system. Some encryption techniques can be adopted, but it is also necessary to verify the reliability of nodes that sense, aggregate,...
Wireless sensor networks (WSNs) have been of high interest during the past couple of years. One of the most important aspect of WSN research is location estimation. As a good solution of fine grained localization Reichenbach et al. introduced the distributed least squares (DLS) algorithm, which splits the costly localization process in a complex precalculation and a simple postcalculation which is...
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