Advanced Sequence-Based Localization Algorithm in Wireless Sensor Networks

2014 ◽  
Vol 651-653 ◽  
pp. 387-390 ◽  
Author(s):  
Fu Bin Zhou ◽  
Shao Li Xue

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.

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaogang Qi ◽  
Xiaoke Liu ◽  
Lifang Liu

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.


2017 ◽  
Vol 13 (09) ◽  
pp. 69 ◽  
Author(s):  
Lianjun Yi ◽  
Miaochao Chen

<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>


Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4152
Author(s):  
Sana Messous ◽  
Hend Liouane ◽  
Omar Cheikhrouhou ◽  
Habib Hamam

As localization represents the main backbone of several wireless sensor networks applications, several localization algorithms have been proposed in the literature. There is a growing interest in the multi-hop localization algorithms as they permit the localization of sensor nodes even if they are several hops away from anchor nodes. One of the most famous localization algorithms is the Distance Vector Hop (DV-Hop). Aiming to minimize the large localization error in the original DV-Hop algorithm, we propose an improved DV-Hop algorithm in this paper. The distance between unknown nodes and anchors is estimated using the received signal strength indication (RSSI) and the polynomial approximation. Moreover, the proposed algorithm uses a recursive computation of the localization process to improve the accuracy of position estimation. Experimental results show that the proposed localization technique minimizes the localization error and improves the localization accuracy.


Author(s):  
Fengrong Han ◽  
Izzeldin Ibrahim Mohamed Abdelaziz ◽  
Xinni Liu ◽  
Kamarul Hawari Ghazali ◽  
Hao Wang

Location information is prerequisite for wireless sensor networks (WSNs) monitoring and control applications, since there is no meaning without position information for collected data. Distance vector hop (DV-Hop) localization algorithm as the typical range-free algorithm that has been widely applied in various applications. Nowadays, the research on range-free localization for WSNs is mostly based on two-dimensional (2D) space. Hence, there are few surveys concentrated on range-free localization in three-dimensional (3D) WSNs. This motivated us to present an extensive overview of enhanced DV-Hop localization algorithms in 3D WSNs. This paper focused on critical challenge between 2D and 3D in localization model, representative range-free 3D localization technique surveys. Moreover, a comprehensive taxonomy of most essential enhanced methods applied in 3D DV-Hop is illustrated. A considerable comparison in term of localization error, computational complexity and node type is given. Future research directions dealing with localization under 3D DV-Hop is also discussed.


2012 ◽  
Vol 8 (1) ◽  
pp. 829253 ◽  
Author(s):  
Yu Liu ◽  
Xiao Yi ◽  
You He

Self-localization of sensor nodes is one of the key issues in wireless sensor networks. Based on the analysis of traditional range-free algorithms such as centroid and APIT (approximate perfect point in triangulation test) schemes, the effect of random deployment of all nodes on node localization is researched. And then, an improved centroid localization algorithm (ICLA) based on APIT and the quality of perpendicular bisector is proposed. In ICLA, nodes are categorized into several kinds and localized, respectively. Extensive simulation results indicate that ICLA obtains a better localization result in random topology networks without any additional hardware. Therefore, ICLA can be an alternate solution for the node self-localization problem in large-scale wireless sensor networks.


Author(s):  
Abderrahim Beni Hssane ◽  
Moulay Lahcen Hasnaoui ◽  
Said Benkirane ◽  
Driss El Ouadghiri ◽  
Mohamed Laghdir

Many applications in Wireless Sensor Networks (WSNs) must know the position of sensor nodes in the network. That is, information from the sensors is useful only if node location information is also available. Additionally, some routing protocols use position to determine viable routes. Several localization algorithms have been proposed which can be categorized as: range-based and range-free algorithms. In this paper, the authors propose an Optimized DV-Hop (ODV-Hop), a localization range-free algorithm. The authors have used a new formula for computing the optimal hope size and used Householder algorithm for solving least square localization problem. Finally, simulation results show that the ODV-Hop achieves good location accuracy than normal DV-Hop.


2013 ◽  
Vol 9 (3) ◽  
pp. 1153-1161
Author(s):  
Basavaraj K Madagouda ◽  
Varsha M Patil ◽  
Pradnya Godse

The accuracy of localization is a significant criterion to evaluate the practical utility of localization algorithm in wireless sensor networks (WSN). In mostly localization algorithms, one of the main methods to improve localization accuracy is to increase the number of anchor nodes. But the number of anchor nodes is always limited because of the hardware restrict, such as cost, energy consumption and so on. In this paper, we propose a novel which uses forwarding a query message in flooding technique for localization using anchor nodes and once a node localized it acts as virtual anchor node and it helps to localize remaining sensor nodes. It is scheme to increase and upgrade the virtual anchor nodes, while the real number of physical anchors is the same as before.


Author(s):  
Amit Sharma ◽  
Pradeep K. Singh

Background: In Wireless Sensor Networks, Localization is the most dynamic field for research. The data extracted from the sensor nodes that carries physical location information is very much helpful in WSNs as it is useful in major applications such as for the purpose of monitoring of any environment, tracking and for the detection purpose. Localization is known as the estimation of unknown node locations and its positions by communicating through localized nodes as well as unlocalized nodes. Objective: The aim of this study is to present classification of various localization algorithms and to compare them. Methods: The prime consideration is to know that how localization affects the network lifetime and how these algorithms work for increasing the lifetime of a network in a severe. Results: This paper also aims for finding the position of the node with respect to range based, anchor based and distributed localization techniques for harsh environments. Additionally, this paper also features the concern that occurs with these localization techniques. Conclusion: The technique that gives highly accurate location coordinates and having less hardware cost is distributed RSSI based localization algorithm.


2011 ◽  
Vol 8 (4) ◽  
pp. 953-972 ◽  
Author(s):  
Qingji Qian ◽  
Xuanjing Shen ◽  
Haipeng Chen

Sensor node localization is the basis for the entire wireless sensor networks. Because of restricted energy of the sensor nodes, the location error, costs of communication and computation should be considered in localization algorithms. DV-Hop localization algorithm is a typical positioning algorithm that has nothing to do with distance. In the isotropic dense network, DV-Hop can achieve position more precisely, but in the random distribution network, the node location error is great. This paper summed up the main causes of error based on the analysis on the process of the DV-Hop algorithm, aimed at the impact to the location error which is brought by the anchor nodes of different position and different quantity, a novel localization algorithm called NDVHop_Bon (New DV-Hop based on optimal nodes) was put forward based on optimal nodes, and it was simulated on Matlab. The results show that the new proposed location algorithm has a higher accuracy on localization with a smaller communication radius in the circumstances, and it has a wider range of applications.


Author(s):  
Amirhosein Hajihoseini ◽  
Seyed Ali Ghorashi

<p>Localization is an important issue for wireless sensor networks. Target localization has attracted many researchers who work on location based services such as navigation, public transportation and so on. Localization algorithms may be performed in a centralized or distributed manner. In this paper we apply diffusion strategy to the Gauss Newton method and introduce a new distributed diffusion based target localization algorithm for wireless sensor networks. In our proposed method, each node knows its own location and estimates the location of target using received signal strength. Then, all nodes cooperate with their neighbors and share their measurements to improve the accuracy of their decisions. In our proposed diffusion based algorithm, each node can localize target individually using its own and neighbor’s measurements, therefore, the power consumption decreases. Simulation results confirm that our proposed method improves the accuracy of target localization compared with alternative distributed consensus based target localization algorithms.  Our proposed algorithm is also shown that is robust against network topology and is insensitive to uncertainty of sensor nodes’ location.</p>


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