scholarly journals Anchor Density Minimization for Localization in Wireless Sensor Network (WSN)

2021 ◽  
Author(s):  
Nour Zaarour ◽  
Nadir Hakem ◽  
NahiKandil
Keyword(s):  
Wireless Sensor Networks ◽  
A Priori ◽  
High Accuracy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Random String ◽  
Trade Off ◽  
Localization Accuracy ◽  
Anchor Nodes ◽  
Good Trade

In wireless sensor networks (WSN) high-accuracy localization is crucial for both of WNS management and many other numerous location-based applications. Only a subset of nodes in a WSN is deployed as anchor nodes with their locations a priori known to localize unknown sensor nodes. The accuracy of the estimated position depends on the number of anchor nodes. Obviously, increasing the number or ratio of anchors will undoubtedly increase the localization accuracy. However, it severely constrains the flexibility of WSN deployment while impacting costs and energy. This paper aims to drastically reduce anchor number or ratio of anchor in WSN deployment and ensures a good trade-off for localization accuracy. Hence, this work presents an approach to decrease the number of anchor nodes without compromising localization accuracy. Assuming a random string WSN topology, the results in terms of anchor rates and localization accuracy are presented and show significant reduction in anchor deployment rates from 32% to 2%.

scholarly journals Localization of Sensor Nodes using Flooding in Wireless Sensor Networks

2013 ◽  
Vol 9 (3) ◽  
pp. 1153-1161
Author(s):  
Basavaraj K Madagouda ◽  
Varsha M Patil ◽  
Pradnya Godse
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Real Number ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Localization Algorithms ◽  
Anchor Nodes

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.

Improved DV-Hop Localization Scheme for Randomly Deployed WSNs

2020 ◽  
Vol 10 (1) ◽  
pp. 94-109 ◽  
Author(s):  
Rekha Goyat ◽  
Mritunjay Kumar Rai ◽  
Gulshan Kumar ◽  
Hye-Jin Kim ◽  
Se-Jung Lim
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Research Area ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Error ◽  
Anchor Nodes ◽  
Least Energy ◽  
Range Free

Background: Wireless Sensor Networks (WSNs) is considered one of the key research area in the recent. Various applications of WSNs need geographic location of the sensor nodes. Objective: Localization in WSNs plays an important role because without knowledge of sensor nodes location the information is useless. Finding the accurate location is very crucial in Wireless Sensor Networks. The efficiency of any localization approach is decided on the basis of accuracy and localization error. In range-free localization approaches, the location of unknown nodes are computed by collecting the information such as minimum hop count, hop size information from neighbors nodes. Methods: Although various studied have been done for computing the location of nodes but still, it is an enduring research area. To mitigate the problems of existing algorithms, a range-free Improved Weighted Novel DV-Hop localization algorithm is proposed. Main motive of the proposed study is to reduced localization error with least energy consumption. Firstly, the location information of anchor nodes is broadcasted upto M hop to decrease the energy consumption. Further, a weight factor and correction factor are introduced which refine the hop size of anchor nodes. Results: The refined hop size is further utilized for localization to reduces localization error significantly. The simulation results of the proposed algorithm are compared with other existing algorithms for evaluating the effectiveness and the performance. The simulated results are evaluated in terms localization error and computational cost by considering different parameters such as node density, percentage of anchor nodes, transmission range, effect of sensing field and effect of M on localization error. Further statistical analysis is performed on simulated results to prove the validation of proposed algorithm. A paired T-test is applied on localization error and localization time. The results of T-test depicts that the proposed algorithm significantly improves the localization accuracy with least energy consumption as compared to other existing algorithms like DV-Hop, IWCDV-Hop, and IDV-Hop. Conclusion: From the simulated results, it is concluded that the proposed algorithm offers 36% accurate localization than traditional DV-Hop and 21 % than IDV-Hop and 13% than IWCDV-Hop.

scholarly journals Genetic Algorithms for Localization in WSN

2020 ◽  
Vol 9 (5) ◽  
pp. 2397-2401
Keyword(s):  
Wireless Sensor Networks ◽  
Genetic Algorithms ◽  
Bat Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Error ◽  
Node Localization ◽  
Soft Computing Techniques ◽  
Anchor Nodes ◽  
The Mean

In wireless sensor networks, localization is a way to track the exact location of sensor nodes. Occasionally node localization may not be accurate due to the absence or limitation of anchor nodes. To reduce the mean localization error, soft computing techniques such as BAT and bacterial foraging driven bat algorithm (BDBA) are utilized in literature. For better localization with reduced error, in this paper, firefly driven bat algorithm (FDBA) is proposed, which combines the heuristic of firefly and BAT algorithms. Our proposed FDBA algorithm provides better localization in terms of error of 60% and 40 % less error as compared to BAT and BDBA algorithm, respectively.

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 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.

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.

scholarly journals Anchor-Node-Based Distributed Localization with Error Correction in Wireless Sensor Networks

2012 ◽  
Vol 8 (4) ◽  
pp. 975147 ◽  
Author(s):  
Taeyoung Kim ◽  
Minhan Shon ◽  
Mihui Kim ◽  
Dongsoo S. Kim ◽  
Hyunseung Choo
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Estimation Error ◽  
Initial Position ◽  
Wireless Sensor ◽  
Anchor Node ◽  
Localization Accuracy ◽  
Message Transmission ◽  
Transmission Cost ◽  
Anchor Nodes

This paper proposes a scheme to enhance localization in terms of accuracy and transmission overhead in wireless sensor networks. This scheme starts from a basic anchor-node-based distributed localization (ADL) using grid scan with the information of anchor nodes within two-hop distance. Even though the localization accuracy of ADL is higher than that of previous schemes (e.g., DRLS), estimation error can be propagated when the ratio of anchor nodes is low. Thus, after each normal node estimates the initial position with ADL, it checks whether the position needs to be corrected because of the insufficient anchors within two-hop distance, that is, the node is in sparse anchor area. If correction needs, the initial position is repositioned using hop progress by the information of anchor nodes located several hops away so that error propagation is reduced (REP); the hop progress is an estimated hop distance using probability based on the density of sensor nodes. Results via in-depth simulation show that ADL has about 12% higher localization accuracy and about 10% lower message transmission cost than DRLS. In addition, the localization accuracy of ADL with REP is about 30% higher than that of DRLS, even though message transmission cost is increased.

An Improved Sensor Positioning for Wireless Sensor Networks

2014 ◽  
Vol 716-717 ◽  
pp. 1322-1325
Author(s):  
Jin Tao Lin ◽  
Guang Yu Fan ◽  
Wen Hong Liu ◽  
Ying Da Hu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Signal Strength ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Positioning Accuracy ◽  
Positioning Method ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Sensor Positioning

Sensor positioning is a fundamental block in various location-dependent applications of wireless sensor networks. In order to improve the positioning accuracy without increasing the complex and cost of sensor nodes, an improve sensor positioning method is proposed for wireless sensor networks. In the method, after receiving the broadcasting message of the neighboring anchor nodes, the sensor nodes calculate a modifying factor of the change of the signal strength. And they modify the distances between themselves and neighboring anchor nodes with the modifying factor. Simulation results show that the proposed method can obtain a high positioning accuracy.

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 Hexahedral Localization (HL): A Three-Dimensional Hexahedron Localization Based on Mobile Beacons

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Linlan Liu ◽  
Haili Zhang ◽  
Xiaotian Geng ◽  
Xin Shu
Keyword(s):  
Wireless Sensor Networks ◽  
Three Dimensional ◽  
High Accuracy ◽  
Wireless Sensor ◽  
Localization Accuracy ◽  
Localization Scheme ◽  
Future Work ◽  
Range Free ◽  
Mobile Beacons ◽  
Dimensional Range

In wireless sensor networks, localization is one of the fundamental technologies and is essential to its applications. In this paper, we propose a three-dimensional range-free localization scheme named hexahedral localization. In the scheme, the space is divided into a lot of hexahedrons. Then, all the unknown nodes are located by utilizing the perpendicular properties of the trajectory. The contribution of our scheme can be summarized into two points. First, it fills the gap of shortage of three-dimensional localization based on mobile beacons. Second, it brings in the outstanding localization accuracy. The simulation result reveals that this localization scheme has the relative high accuracy. At the end of the paper, the performance and error of our scheme are analyzed in aim of improving in the future work.

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