scholarly journals Secure and Robust 3D Localization in Wireless Sensor Networks

2019 ◽  
Vol 9 (1S) ◽  
pp. 104-111
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Malicious Nodes ◽  
3D Localization ◽  
Secure Localization ◽  
Simulation Results ◽  
Two Phases

The fundamental capacity of a sensor system is to accumulate and forward data to the destination. It is crucial to consider the area of gathered data, which is utilized to sort information that can be procured using confinement strategy as a piece of Wireless Sensor Networks (WSNs).Localization is a champion among the most basic progressions since it agreed as an essential part in various applications, e.g., target tracking. If the client can't gain the definite area information, the related applications can't be skillful. The crucial idea in most localization procedures is that some deployed nodes with known positions (e.g., GPS-equipped nodes) transmit signals with their coordinates so as to support other nodes to localize themselves. This paper mainly focuses on the algorithm that has been proposed to securely and robustly decide thelocation of a sensor node. The algorithm works in two phases namely Secure localization phase and Robust Localization phase. By "secure", we imply that malicious nodes should not effectively affect the accuracy of the localized nodes. By “robust”, we indicate that the algorithm works in a 3D environment even in the presence of malicious beacon nodes. The existing methodologies were proposed based on 2D localization; however in this work in addition to security and robustness, exact localization can be determined for 3D areas by utilizing anefficient localization algorithm. Simulation results exhibit that when compared to other existing algorithms, our proposed work performs better in terms of localization error and accuracy.

scholarly journals Enhancing the Sensor Node Localization Algorithm Based on Improved DV-Hop and DE Algorithms in Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 343 ◽  
Author(s):  
Dezhi Han ◽  
Yunping Yu ◽  
Kuan-Ching Li ◽  
Rodrigo Fernandes de Mello
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Node Localization ◽  
Random Mutation ◽  
Localization Accuracy ◽  
De Algorithm ◽  
Distance Vector

The Distance Vector-Hop (DV-Hop) algorithm is the most well-known range-free localization algorithm based on the distance vector routing protocol in wireless sensor networks; however, it is widely known that its localization accuracy is limited. In this paper, DEIDV-Hop is proposed, an enhanced wireless sensor node localization algorithm based on the differential evolution (DE) and improved DV-Hop algorithms, which improves the problem of potential error about average distance per hop. Introduced into the random individuals of mutation operation that increase the diversity of the population, random mutation is infused to enhance the search stagnation and premature convergence of the DE algorithm. On the basis of the generated individual, the social learning part of the Particle Swarm (PSO) algorithm is embedded into the crossover operation that accelerates the convergence speed as well as improves the optimization result of the algorithm. The improved DE algorithm is applied to obtain the global optimal solution corresponding to the estimated location of the unknown node. Among the four different network environments, the simulation results show that the proposed algorithm has smaller localization errors and more excellent stability than previous ones. Still, it is promising for application scenarios with higher localization accuracy and stability requirements.

A Collaborative Multilateral Localization Algorithm for Wireless Sensor Networks

2013 ◽  
Vol 303-306 ◽  
pp. 201-205
Author(s):  
Shao Ping Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Optimization Method ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Localization Method ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Unknown Node

Localization technology is one of the key supporting technologies in wireless sensor networks. In this paper, a collaborative multilateral localization algorithm is proposed to localization issues for wireless sensor networks. The algorithm applies anchor nodes within two hops to localize unknown nodes, and uses Nelder-Mead simplex optimization method to compute coordinates of the unknown nodes. If an unknown node can not be localized through two-hop anchor nodes, it is localized by anchor nodes and localized nodes within two hops through auxiliary iterative localization method. Simulation results show that the localization accuracy of this algorithm is very good, even in larger range errors.

A GPS-Less Cell-Based Localization Technique for Wireless Sensor Networks

2012 ◽  
Vol 601 ◽  
pp. 376-382
Author(s):  
Xue Jun Li
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Power Level ◽  
Wireless Sensor ◽  
Transmission Power ◽  
Localization Algorithm ◽  
Localization Technique ◽  
Simulation Results

This paper presents a localization algorithm, namely Circle Based Localization (CBL) for GPS-less wireless sensor networks. CBL works by finding the centroid of intersection of any two circles. Furthermore, we study the effect of power level mismatch among anchors. Simulation results show that CBL can significantly improve the accuracy by 5% while reducing the transmission power of anchors.

scholarly journals Subjective Logic-Based Anomaly Detection Framework in Wireless Sensor Networks

2012 ◽  
Vol 8 (1) ◽  
pp. 482191 ◽  
Author(s):  
Jinhui Yuan ◽  
Hongwei Zhou ◽  
Hong Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Anomaly Detection ◽  
Sensor Node ◽  
Wireless Sensor ◽  
Data Simulation ◽  
Subjective Logic ◽  
Simulation Results ◽  
Anomaly Score

In existing anomaly detection approaches, sensor node often turns to neighbors to further determine whether the data is normal while the node itself cannot decide. However, previous works consider neighbors' opinions being just normal and anomalous, and do not consider the uncertainty of neighbors to the data of the node. In this paper, we propose SLAD (subjective logic based anomaly detection) framework. It redefines opinion deriving from subjective logic theory which takes the uncertainty into account. Furthermore, it fuses the opinions of neighbors to get the quantitative anomaly score of the data. Simulation results show that SLAD framework improves the performance of anomaly detection compared with previous works.

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.

A Range-Based Secure Localization Algorithm for Wireless Sensor Networks

2019 ◽  
Vol 19 (2) ◽  
pp. 785-796 ◽  
Author(s):  
Xingcheng Liu ◽  
Shaohua Su ◽  
Feng Han ◽  
Yitong Liu ◽  
Zhihong Pan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Secure Localization

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>

Correlation between Estimation Error and Possible Region in Localization Algorithms

2012 ◽  
Vol 457-458 ◽  
pp. 1514-1520
Author(s):  
Shi Hao Yan ◽  
Jian Ping Xing ◽  
De Qiang Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Estimation Error ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Estimation Errors ◽  
Localization Algorithms ◽  
Localization Precision ◽  
Simulation Results ◽  
Definite Correlation

Many localization algorithms in wireless sensor networks mention possible regions to increase the degree of localization precision. In this paper, we present the definite correlation between the estimation error and the possible region. The estimation error, which is the most important indictor to judge the performance of a localization algorithm, is proportional to the square root of the area of the possible region and the factor of proportionality relates to the shape of the possible region. We also propose two applications of the definite correlation, including estimation errors detection and energy conservation. The simulation results show that the definite correlation is suitable for all kinds of possible regions and it is feasible to detect estimation errors and conserve energy when we fix reasonable areas of possible regions in wireless sensor networks.

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