scholarly journals Iterative L-M Algorithm in WSN – Utilizing Modifying Average Hopping Distances

2017 ◽  
Vol 13 (10) ◽  
pp. 4 ◽  
Author(s):  
Xin Qiao ◽  
Han-Sheng Yang ◽  
Zheng-Chuang Wang
Keyword(s):  
Data Exchange ◽  
Weighted Average ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Simulation Environment ◽  
Hop Count ◽  
Positioning Accuracy ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Unknown Node

Wireless sensor networks are more and more important for various applications. Localization plays an important role in WSN. In this article,<strong> </strong>Aiming at the large errors that the DV—Hop localization algorithm have in net topology with randomly-distributed nodes, this paper proposed a CLDV-Hop algorithm in DV-Hop based on modifying average hopping distances. Firstly, hop count threshold is set to optimize the anchor node when data exchange. Then, according to the minimum mean square criteria and unknown nodes nearest three anchor nodes weighted average hop distance are selected as its average hop distance. Finally, L-M algorithm is used to optimize the coordinate of unknown node estimated by least squares. The simulation results show that, without increasing the overhead and the same conditions as the simulation environment, CLDV-Hop algorithm has higher positioning accuracy than existing improved algorithms, and compared with DV-Hop algorithm accuracy is improved by about 33% - 41%.

Localization Algorithm Based on DV-HOP for Wireless Sensor Network

2011 ◽  
Vol 128-129 ◽  
pp. 909-913
Author(s):  
Yu Hu ◽  
Xue Mei Li
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Weighted Average ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Positioning Accuracy ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Improved Algorithm

An improved DV-HOP localization algorithm is proposed in the paper, aiming at the traditional DV-HOP localization algorithm. The improved algorithm introduces threshold M, it uses the weighted average hop distances of anchor nodes within M hops to calculate the average hop distance of unknown nodes. In addition, the positioning results are corrected in the improved algorithm. The simulation results show that the improved localization algorithm effectively improves the positioning accuracy compared with the traditional DV-HOP localization algorithm, it is an effective localization algorithm for the wireless sensor networks.

Based on RSSI Ranging Technology for DV-Hop Localization Algorithm of Wireless Sensor Network

2012 ◽  
Vol 442 ◽  
pp. 360-365 ◽  
Author(s):  
Yang Jun Zhong
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Approximate Calculation ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Positioning Accuracy ◽  
Original Algorithm ◽  
Approximate Distance ◽  
Anchor Nodes ◽  
Simulation Results

For the DV-Hop algorithm of wireless sensor networks,there is an error arising problem that anchor nodes and location node hop distance is only an approximate calculation. A method based on the original Algorithm introducing RSSI ranging technique is proposed.Using RSSI ranging technology,we accord that if the anchor nodes is only a hop away from the location node,then decide whether using the DV-Hop algorithm to approach to the approximate distance between them. Simulation results show that the algorithm can effectively improve the error problems of calculating the hop distance between the anchor nodes and the location nodes, meanwhile improve the positioning accuracy of the node.

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.

DV-Hop Localization Algorithm Based on Distance Geometry Constrain

2012 ◽  
Vol 433-440 ◽  
pp. 4009-4013
Author(s):  
Jun Gang Zheng ◽  
Cheng Dong Wu ◽  
Hao Chu ◽  
Yang Xu
Keyword(s):  
Dimensional Space ◽  
Distance Geometry ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Node Localization ◽  
Positioning Accuracy ◽  
Key Technologies ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Error Of Measurement

Node localization is one of the key technologies in wireless sensor networks,DV-Hop algorithm is wildly usded .The main DV-Hop localization error is the distance between unknown nodes ande anchor nodes.In this paper, The distance geometry constrain in two-dimensional space has been applied to reduce the error of measurement ,which is the distance between unknown nodes and anchor nodes. Simulation results show that this localization algorithm is effective ,which improves the positioning accuracy.

scholarly journals An Improved DV-Hop Localization Algorithm Based on Bat Algorithm

2016 ◽  
Vol 16 (1) ◽  
pp. 89-98 ◽  
Author(s):  
Xiaoying Yang ◽  
Wanli Zhang
Keyword(s):  
Average Distance ◽  
Bat Algorithm ◽  
Localization Algorithm ◽  
Hop Count ◽  
Intelligent Optimization ◽  
Intelligent Optimization Algorithm ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Unknown Node ◽  
Additional Hardware

Abstract In the DV-Hop algorithm, the average distance per hop is one of the factors that affect the accuracy of the positioning. In this paper, an improved DV-Hop localization algorithm based on bat algorithm (BAD-Hop) is proposed to solve the error which is brought by the average distance per hop. In BAD-Hop algorithm, bat algorithm which is a kind of intelligent optimization algorithm with good performance is introduced into DV-Hop localization algorithm to calculate average distance per hop of anchor nodes. Firstly, the average distance per hop of anchor node is calculated by using bat algorithm, which makes it closer to the actual value. Then the average distance per hop of the unknown node is weighted by using the average distance per hop of anchor nodes which hop-count is less than or equal to 3 to reduce errors caused by average distance per hop. Simulation results show that the improved algorithm can effectively reduce the positioning error without additional hardware.

scholarly journals Localization Algorithm Based on Iterative Centroid Estimation for Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Rui Jiang ◽  
Xin Wang ◽  
Li Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Anchor Node ◽  
Centroid Estimation ◽  
Anchor Nodes ◽  
Localization Precision ◽  
Unknown Node ◽  
Received Signal Strength Indication

According to the application of range-free localization technology for wireless sensor networks (WSNs), an improved localization algorithm based on iterative centroid estimation is proposed in this paper. With this methodology, the centroid coordinate of the space enclosed by connected anchor nodes and the received signal strength indication (RSSI) between the unknown node and the centroid are calculated. Then, the centroid is used as a virtual anchor node. It is proven that there is at least one connected anchor node whose distance from the unknown node must be farther than the virtual anchor node. Hence, in order to reduce the space enclosed by connected anchor nodes and improve the location precision, the anchor node with the weakest RSSI is replaced by this virtual anchor node. By applying this procedure repeatedly, the localization algorithm can achieve a good accuracy. Observing from the simulation results, the proposed algorithm has strong robustness and can achieve an ideal performance of localization precision and coverage.

Intelligent Three-dimensional Node Localization Algorithm Using Dynamic Path Planning

2021 ◽  
Vol 14 ◽  
Author(s):  
Songhao Jia ◽  
Cai Yang ◽  
Xing Chen ◽  
Yan Liu ◽  
Fangfang Li
Keyword(s):  
Path Planning ◽  
Dynamic Stiffness ◽  
Three Dimensional ◽  
Localization Algorithm ◽  
Node Localization ◽  
Positioning Accuracy ◽  
Dynamic Path Planning ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Dynamic Path

Background: In the applications of wireless sensor network technology, three-dimensional node location technology is crucial. The process of node localization has some disadvantages, such as the uneven distribution of anchor nodes and the high cost of the network. Therefore, the mobile anchor nodes are introduced to effectively solve accurate positioning. Objective: Considering the estimated distance error, the received signal strength indication technology is used to optimize the measurement of the distance. At the same time, dynamic stiffness planning is introduced to increase virtual anchor nodes. Moreover, the bird swarm algorithm is also used to solve the optimal location problem of nodes. Method: Firstly, the dynamic path is introduced to increase the number of virtual anchor nodes. At the same time, the improved RSSI distance measurement technology is introduced to the node localization. Then, an intelligent three-dimensional node localization algorithm based on dynamic path planning is proposed. Finally, the proposed algorithm is compared with similar algorithms through simulation experiments. Results: Simulation results show that the node coordinates obtained by the proposed algorithm are more accurate, and the node positioning accuracy is improved. The execution time and network coverage of the algorithm are better than similar algorithms. Conclusion: The proposed algorithm significantly improves the accuracy of node positioning. However, the traffic of the algorithm is increased. A little increase in traffic in exchange for positioning accuracy is worthy of recognition. The simulation results show that the proposed algorithm is robust and can be implemented and promoted in the future.

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.

PACMLA: A Localization Algorithm Based on Permutation and Combination Midnormal for Wireless Sensor Networks

2013 ◽  
Vol 475-476 ◽  
pp. 564-568
Author(s):  
Wei Yong Jiang ◽  
Pin Wan ◽  
Yong Hua Wang ◽  
Dong Liang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Cost ◽  
Wireless Sensor ◽  
Data Sets ◽  
Localization Algorithm ◽  
Anchor Nodes ◽  
Unknown Node ◽  
Number Of Iterations ◽  
Range Free

Localization of sensors is one key technique in wireless sensor networks (WSN).Because the midnormal-based localization algorithm (MBLA) has shortcomings such as low accuracy, relatively large number of iterations, a localization algorithm based on permutation and combination midnormal (PACMLA) for WSN is proposed. Nodes are divided into anchor nodes and unknown nodes. In its own communication range, unknown node can communicate with anchor nodes. In PACMLA algorithm, the unknown node communicates with the anchor nodes in turn, and collects their coordinate information and RSSI value. Then by comparing the RSSI values received by unknown node, these RSSI values are formed an array in accordance with the order from small to large. Then starting from the first value of the RSSI array, each of these values and the value behind them will be combined into data sets. Finally, according to corresponding coordinate information of the RSSI value in the data sets, we will determine the position of the unknown node by Point In Which Side (PIWS) determination. In addition, our algorithm is a kind of Range-free algorithm, and it can cuts down the node energy cost. The experiment results illustrate that the PACMLA algorithm has lower error and higher accuracy.

Centroid Localization Algorithm Based on the Anchor Nodes Cellular Distribution

2013 ◽  
Vol 475-476 ◽  
pp. 579-582 ◽  
Author(s):  
Dong Yao Zou ◽  
Teng Fei Han ◽  
Dao Li Zheng ◽  
He Lv
Keyword(s):  
Wireless Sensor Networks ◽  
Cellular Network ◽  
Wireless Sensor ◽  
Cellular Distribution ◽  
Localization Algorithm ◽  
Matlab Simulation ◽  
Node Localization ◽  
Key Technologies ◽  
Anchor Nodes ◽  
Simulation Results

The node localization is one of the key technologies in wireless sensor networks. To the accurate positioning of the nodes as the premise and foundation, this paper presents a centroid localization algorithm based on Cellular network. First, the anchor nodes are distributed in a regular hexagonal cellular network. Unknown nodes collect the RSSI of the unknown nodes nearby, then select the anchor nodes whose RSSI is above the threshold. Finally, the average of these anchor nodes coordinates is the positioning results. MATLAB simulation results show that localization algorithm is simple and effective, it applies to the need for hardware is relatively low.

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