scholarly journals Wireless Sensor Network Dynamic Mathematics Modeling and Node Localization

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Xiaoyang Liu ◽  
Chao Liu

With the rapid development of wireless sensor network (WSN) technology and its localization method, localization is one of the basic services for data collection in WSN. The localization accuracy often depends on the accuracy of distance estimation. Because of the constraint in size, power, and cost of sensor nodes, the investigation of efficient location algorithms which satisfy the basic accuracy requirement for WSN meets new challenges. This paper proposes a novel intelligent node localization algorithm in WSN based on beacon nodes to improve the precision in location estimation. Firstly, system model of WSN node localization is constructed according to the WSN environment. Then traditional WSN node localization methods such as DV-HOP, GA, and PSO are studied. Localization algorithm of WSN is proposed by using dynamic mathematics modeling. And the result of simulation, which is compared to the traditional algorithm, indicated that this algorithm is better to improve the accuracy and coverage of WSN. The simulation results show that the performance of the proposed WSN location algorithm is better than the traditional localization algorithms.

2017 ◽  
Vol 13 (07) ◽  
pp. 57
Author(s):  
Min Wang

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">For exploring wireless sensor network - a self-organized network, a new node location algorithm based on statistical uncorrelated vector (SUV) model, namely SUV location algorithm, is proposed. The algorithm, by translating the node coordinate, simplifies the solution to double center coordinate matrix, and gets the coordinate inner product matrix; then it uses statistical uncorrelated vectors to reconstruct the coordinates of the inner product matrix and remove the correlation of inner matrix of coordinates caused by the ranging error, so as to reduce the impact of ranging error on subsequent positioning accuracy. The experimental results show that the proposed algorithm does not consider the network traffic, bust still has good performance in localization. At last, it is concluded that reducing the amount of communication of sensor nodes is beneficial to prolong the service life of the sensor nodes, thus increasing the lifetime of the whole network.</span>


2014 ◽  
Vol 14 (5) ◽  
pp. 98-107 ◽  
Author(s):  
Jiang Xu ◽  
Huanyan Qian ◽  
Huan Dai ◽  
Jianxin Zhu

Abstract In this paper a new wireless sensor network localization algorithm, based on a mobile beacon and TSVM (Transductive Support Vector Machines) is proposed, which is referred to as MTSVM. The new algorithm takes advantage of a mobile beacon to generate virtual beacon nodes and then utilizes the beacon vector produced by the communication between the nodes to transform the problem of localization into one of classification. TSVM helps to minimize the error of classification of unknown fixed nodes (unlabeled samples). An auxiliary mobile beacon is designed to save the large volumes of expensive sensor nodes with GPS devices. As shown by the simulation test, the algorithm achieves good localization performance.


2007 ◽  
Vol 04 (01) ◽  
pp. 77-89 ◽  
Author(s):  
WANMING CHEN ◽  
HUAWEI LIANG ◽  
TAO MEI ◽  
ZHUHONG YOU ◽  
SHIFU MIAO ◽  
...  

Global Positioning System (GPS) is often used as a main information source for robot localization and navigation. However, it cannot be used in room or in field complex environment because of the bad signal there. To solve this problem, the authors designed and implemented a specific wireless sensor network (WSN) to provide information about the environment and indicate path for robot navigation. A two-stage auto-adaptive route selecting mechanism of the WSN was proposed to facilitate data relaying in localization and the robot's navigation. A low complexity localization algorithm was used to localize both the nodes and the robot. An indirect communication method was designed to make the communication between the WSN and the robot possible. In addition, a robot navigation method was proposed based on the wireless sensor network. In this method, the robot did not need to obtain the environment information; the wireless sensor nodes collected and fused the distributed information and then indicate a path for the robot. Experiments showed that the wireless sensor network can result in obstacle avoidance navigation, and can implement the online navigation.


2017 ◽  
Vol 13 (05) ◽  
pp. 4 ◽  
Author(s):  
Peng An

In the wireless sensor network, there is a consistent one-to-one match between the information collected by the node and the location of the node. Therefore, it attempts to determine the location of unknown nodes for wireless sensor networks. At present, there are many kinds of node localization methods. Because of the distance error, hardware level, application environment and application costs and other factors, the positioning accuracy of various node positioning methods is not in complete accord. The objective function is established and algorithm simulation experiments are carried out to make a mobile ronot node localization.  The experimnettal results showed that  the proposed algorithm can achieve higher localization precision in fewer nodes. In addition, the localization algorithm was compared with the classical localization algorithm. In conclusion, it is verified that the localization algorithm proposed in this paper has higher localization accuracy than the traditional classical localization algorithm when the number of nodes is larger than a certain number


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