scholarly journals A Localization Algorithm Based on AOA for Ad-Hoc Sensor Networks

2012 ◽  
Vol 8 (1) ◽  
pp. 61-72 ◽  
Author(s):  
Yang Sun Lee ◽  
Jang Woo Park ◽  
Leonard Barolli
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Ad Hoc ◽  
Incident Angle ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Multiple Paths ◽  
Asset Monitoring ◽  
Ad Hoc Sensor Networks

Knowledge of positions of sensor nodes in Wireless Sensor Networks (WSNs) will make possible many applications such as asset monitoring, object tracking and routing. In WSNs, the errors may happen in the measurement of distances and angles between pairs of nodes in WSN and these errors will be propagated to different nodes, the estimation of positions of sensor nodes can be difficult and have huge errors. In this paper, we will propose localization algorithm based on both distance and angle to landmark. So, we introduce a method of incident angle to landmark and the algorithm to exchange physical data such as distances and incident angles and update the position of a node by utilizing multiple landmarks and multiple paths to landmarks.

scholarly journals Time-selective data fusion for in-network processing in ad hoc wireless sensor networks

2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881130 ◽  
Author(s):  
Jaanus Kaugerand ◽  
Johannes Ehala ◽  
Leo Mõtus ◽  
Jürgo-Sören Preden
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Fusion ◽  
Data Streams ◽  
Ad Hoc ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Temporal Consistency ◽  
Variable Delays

This article introduces a time-selective strategy for enhancing temporal consistency of input data for multi-sensor data fusion for in-network data processing in ad hoc wireless sensor networks. Detecting and handling complex time-variable (real-time) situations require methodical consideration of temporal aspects, especially in ad hoc wireless sensor network with distributed asynchronous and autonomous nodes. For example, assigning processing intervals of network nodes, defining validity and simultaneity requirements for data items, determining the size of memory required for buffering the data streams produced by ad hoc nodes and other relevant aspects. The data streams produced periodically and sometimes intermittently by sensor nodes arrive to the fusion nodes with variable delays, which results in sporadic temporal order of inputs. Using data from individual nodes in the order of arrival (i.e. freshest data first) does not, in all cases, yield the optimal results in terms of data temporal consistency and fusion accuracy. We propose time-selective data fusion strategy, which combines temporal alignment, temporal constraints and a method for computing delay of sensor readings, to allow fusion node to select the temporally compatible data from received streams. A real-world experiment (moving vehicles in urban environment) for validation of the strategy demonstrates significant improvement of the accuracy of fusion results.

An Enhanced DV-Hop Localization Algorithm for Wireless Sensor Networks

2012 ◽  
Vol 2 (2) ◽  
pp. 16-35 ◽  
Author(s):  
Shrawan Kumar ◽  
D. K. Lobiyal
Keyword(s):  
Wireless Sensor Networks ◽  
Linear Programming ◽  
Sensor Networks ◽  
Problem Formulation ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Location Accuracy ◽  
Localization Accuracy ◽  
Error Terms

Obtaining precise location of sensor nodes at low energy consumption, less hardware requirement, and little computation is a challenging task. As one of the well-known range-free localization algorithm, DV-Hop can be simply implemented in wireless sensor networks, but it provides poor localization accuracy. Therefore, in this paper, the authors propose an enhanced DV-Hop localization algorithm that provides good localization accuracy without requiring additional hardware and communication messages in the network. The first two steps of proposed algorithm are similar to the respective steps of the DV-Hop algorithm. In the third step, they first separate error terms (correction factors) of the estimated distance between unknown node and anchor node. The authors then minimize these error terms by using linear programming to obtain better location accuracy. Furthermore, they enhance location accuracy of nodes by introducing weight matrix in the objective function of linear programming problem formulation. Simulation results show that the performance of our proposed algorithm is superior to DV-Hop algorithm and DV-Hop–based algorithms in all considered scenarios.

scholarly journals Online Sequential DV-Hop Localization Algorithm for Wireless Sensor Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Sana Messous ◽  
Hend Liouane
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Average Distance ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Node Localization ◽  
Multihop Wireless ◽  
Distance Vector ◽  
Node Position

One of the main issues of wireless sensor networks is localization. Besides, it is important to track and analyze the sensed information. The technique of localization can calculate node position with the help of a set of designed nodes, denoted as anchors. The set density of these anchors may be incremented or decremented because of many reasons such as maintenance, lifetime, and breakdown. The well-known Distance Vector Hop (DV-Hop) algorithm is a suitable solution for localizing nodes having few neighbor anchors. However, existing DV-Hop-based localization methods have not considered the problem of anchor breakdown which may happen during the localization process. In order to avoid this issue, an Online Sequential DV-Hop algorithm is proposed in this paper to sequentially calculate positions of nodes and improve accuracy of node localization for multihop wireless sensor networks. The algorithm deals with the variation of the number of available anchors in the network. We note that DV-Hop algorithm is used in this article to process localization of nodes by a new optimized method for the estimation of the average distance of hops between nodes. Our proposed localization method is based on an online sequential computation. Compared with the original DV-Hop and other localization methods from the literature, simulation results prove that the proposed algorithm greatly minimizes the average of localization error of sensor nodes.

scholarly journals A Combined Localization Algorithm for Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaogang Qi ◽  
Xiaoke Liu ◽  
Lifang Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
State Of The Art ◽  
Sensor Nodes ◽  
Vehicle Tracking ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Environment And Health ◽  
Anchor Nodes ◽  
Positioning Algorithm

Wireless sensor networks (WSNs) are widely used in various fields to monitor and track various targets by gathering information, such as vehicle tracking and environment and health monitoring. The information gathered by the sensor nodes becomes meaningful only if it is known where it was collected from. Considering that multilateral algorithm and MDS algorithm can locate the position of each node, we proposed a localization algorithm combining the merits of these two approaches, which is called MA-MDS, to reduce the accumulation of errors in the process of multilateral positioning algorithm and improve the nodes’ positioning accuracy in WSNs. It works in more robust fashion for noise sparse networks, even with less number of anchor nodes. In the MDS positioning phase of this algorithm, the Prussian Analysis algorithm is used to obtain more accurate coordinate transformation. Through extensive simulations and the repeatable experiments under diverse representative networks, it can be confirmed that the proposed algorithm is more accurate and more efficient than the state-of-the-art algorithms.

Localization in Wireless Sensor Networks in Beacon Drifting Scenarios

2012 ◽  
Vol 562-564 ◽  
pp. 1234-1239
Author(s):  
Ming Xia ◽  
Qing Zhang Chen ◽  
Yan Jin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Probability Density ◽  
Sensor Nodes ◽  
Density Model ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Scenarios Simulation ◽  
Simulation Results

The beacon drifting problem occurs when the beacon nodes move accidentally after deployment. In this occasion, the localization results of sensor nodes in the network will be greatly affected and become inaccurate. In this paper, we present a localization algorithm in wireless sensor networks in beacon drifting scenarios. The algorithm first uses a probability density model to calculate the location reliability of each node, and in localization it will dynamically choose nodes with highest location reliabilities as beacon nodes to improve localization accuracy in beacon drifting scenarios. Simulation results show that the proposed algorithm achieves its design goals.

scholarly journals An Enhanced Hybrid 3D Localization Algorithm Based on APIT and DV-Hop

2017 ◽  
Vol 13 (09) ◽  
pp. 69 ◽  
Author(s):  
Lianjun Yi ◽  
Miaochao Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Hybrid Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
3D Localization ◽  
Localization Algorithms ◽  
Wide Range

<p>Wireless sensor networks (WSN), as a new method of information collection and processing, has a wide range of applications. Since the acquired data must be bound with the location information of sensor nodes, the sensor localization is one of the supporting technologies of wireless sensor networks. However, the common localization algorithms, such as APIT algorithm and DV-Hop algorithm, have the following problems: 1) the localization accuracy of beacon nodes is not high; 2) low coverage rate in sparse environment. In this paper, an enhanced hybrid 3D localization algorithm is designed with combining the advantages of APIT algorithm and DV-Hop algorithm. The proposed hybrid algorithm can improve the localization accuracy of the beacon nodes in dense environments by reducing the triangles in the triangle interior point test (PIT) and selecting good triangles. In addition, the algorithm can combine the advantages of APIT algorithm and DV-Hop algorithm localization algorithm to calculate the unknown node coordinates, and also improve the location coverage of the beacon nodes in sparse environment. Simulation results show that the proposed hybrid algorithm can effectively improve the localization accuracy of beacon nodes in the dense environment and the location coverage of beacon nodes in sparse environment.</p>

Advanced Sequence-Based Localization Algorithm in Wireless Sensor Networks

2014 ◽  
Vol 651-653 ◽  
pp. 387-390 ◽  
Author(s):  
Fu Bin Zhou ◽  
Shao Li Xue
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Measuring Devices ◽  
Localization Algorithms ◽  
Positioning Algorithm ◽  
Range Free

As an important application of Internet of Things , Wireless Sensor Networks utilized in surveillance and other case.Localization of nodes in wireless sensor networks is the prerequisite and base of target tracking in some surveillance applications, so localization error of sensor nodes is a key. However, due to limited energy, unreliable link and limited communication ranges of sensor nodes, high accurate positioning is difficult to achieve, which made it hot and full of challenging for wireless sensor nodes to localize without any auxiliary facilities. Range-based localization algorithm , could achieve good accuracy but require measuring devices, thus it is not appropriate for large-scale wireless sensor networks.So range-free localization algorithms are more popular.This paper analyses the algorithms in range-free localization,and proposed Advanced Sequence-Based Localization algorithm to improve the performance of positioning algorithm in wireless sensor network.

A Novel Stochastic Localization Algorithm for Sensor Nodes in Wireless Sensor Networks

2010 ◽  
Vol 39 ◽  
pp. 510-516
Author(s):  
Ming Wang ◽  
Shou Jun Bai ◽  
Huan Bao Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Monte Carlo ◽  
Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
The Novel ◽  
Localization Algorithm ◽  
Mobile Wireless ◽  
Monte Carlo Localization ◽  
Mobile Wireless Sensor

Most of the proposed algorithms focus on static networks of sensors with either static or mobile anchors, in which the Monte Carlo localization algorithm is a typical one for localizing nodes in a mobile wireless sensor network. But the radio range being all different or inconstant in this algorithm leads to reduce the accuracy of localization and the efficiency of the algorithm itself. In this article, we propose the novel rang-based stochastic Monte Carlo localization algorithm for wireless sensor networks specifically designed with mobility to improve the accuracy of localization by dealing with the different radio ranges of sensors, and being bound to the narrow sampling area. Our simulation experimental results show that the rang-based stochastic Monte Carlo localization algorithm has improved the accuracy and stability of the estimated locations.

scholarly journals Heuristic Localization Algorithm with a Novel Error Control Mechanism for Wireless Sensor Networks with Few Anchor Nodes

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Yujia Sun ◽  
Xiaoming Wang ◽  
Jiyan Yu ◽  
Yu Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Error Control ◽  
Control Mechanism ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Geometric Feature ◽  
Localization Algorithm ◽  
Anchor Nodes ◽  
Error Control Mechanism

A novel iterative localization algorithm with high accuracy and low anchor node dependency for large-scale wireless sensor networks is proposed in this paper. At each iteration, blind nodes are located using a weighted linear least squares-based algorithm. To prevent errors in the blind nodes from propagating and accumulating throughout the network, an anchor geometric feature-based error control mechanism is used to select the nodes that participate in the localization and to estimate the localization confidence. The simulation results show that the algorithm can be used when only a few anchor nodes are involved. This algorithm is more advanced than traditional methods, which often require a large number of well-placed anchor nodes to operate appropriately. By optimizing the decision parameter v of the algorithm, the average localization error of the algorithm is approximately 0.43 meters. When the ratio of anchor nodes (the ratio of the number of anchor nodes to the number of sensor nodes in the network) is 1.25% (i.e., 5 anchor nodes for 400 sensor nodes), the received signal strength indicator (RSSI) variance is 8 dBm, and the radio range is 50 meters. A comparison of the proposed algorithm with global localization methods, including multidimensional scaling (MDS), semidefinite programming (SDP), and shortest-path access (SPA), shows that the proposed algorithm achieves higher location accuracy and stability when the number of anchor nodes is varied. The efficiency of the proposed localization algorithm is evaluated in a real sensor network, and the accuracy is high and robust to radio channel variance.

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