scholarly journals A Localization Algorithm of Wireless Sensor Network Based on Statistical Uncorrelated Vector

2017 ◽  
Vol 13 (07) ◽  
pp. 57
Author(s):  
Min Wang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Inner Product ◽  
Localization Algorithm ◽  
Product Matrix ◽  
Ranging Error ◽  
Location Algorithm ◽  
The Impact

<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>

scholarly journals Wireless Sensor Network Localization Based On A Mobile Beacon And Tsvm

2014 ◽  
Vol 14 (5) ◽  
pp. 98-107 ◽  
Author(s):  
Jiang Xu ◽  
Huanyan Qian ◽  
Huan Dai ◽  
Jianxin Zhu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Support Vector ◽  
Localization Algorithm ◽  
Sensor Network Localization ◽  
Network Localization ◽  
Gps Devices ◽  
Mobile Beacon

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.

DESIGN AND IMPLEMENTATION OF WIRELESS SENSOR NETWORK FOR ROBOT NAVIGATION

2007 ◽  
Vol 04 (01) ◽  
pp. 77-89 ◽  
Author(s):  
WANMING CHEN ◽  
HUAWEI LIANG ◽  
TAO MEI ◽  
ZHUHONG YOU ◽  
SHIFU MIAO ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Robot Navigation ◽  
Information Source ◽  
Low Complexity ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Distributed Information ◽  
Communication Method

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.

scholarly journals Application of Ranging Difference Location Algorithm in Wireless Sensor Network Location

2017 ◽  
Vol 13 (07) ◽  
pp. 81
Author(s):  
Bo Xiang
Keyword(s):  
Sensor Network ◽  
Hyperbolic Equations ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Font Size ◽  
Network Location ◽  
Error Location ◽  
Ranging Error ◽  
Localization Performance ◽  
Location Algorithm

<span style="color: black; font-family: 'Times New Roman',serif; font-size: 10pt; mso-ansi-language: EN-US; mso-fareast-font-family: 'Times New Roman'; mso-fareast-language: DE; mso-bidi-language: AR-SA; mso-themecolor: text1;" lang="EN-US">A kind of location technologies are developed used in the sensor network monitoring, the existing RSSI location algorithm are analyzed, and a localization method is proposed based on the SSDOA ranging difference method. hyperbolic equations are constructed and Chan's algorithm is used to solve the coordinates of unknown nodes. The simulation model of ranging error location algorithm is established by MATLAB. By analyzing the effect of ranging accuracy on positioning accuracy, the positioning performance of classical RSSI localization algorithm is compared. The results show that the WSN localization algorithm based on the SSDOA has a good localization performance and can meet the localization requirements of some WSN applications. Based on the above finding, It is concluded that Chan's algorithm is suitable for wireless sensor networks based on TDOA localization algorithm.</span>

scholarly journals Energy Efficiency in Wireless Sensor Network using Randomized Switching for Maximizing Lifetime

2019 ◽  
Vol 8 (6) ◽  
pp. 1058-1061
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Threshold Energy ◽  
Life Time ◽  
Distributed Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Switching Algorithm

Wireless Sensor Network is distributed networks of sensors which have the ability to sense, process and communicate. Sensor nodes are also responsible for collection of data. Due to the limited battery power of sensor node energy consumption is an essential issue. To reduce the energy consumption balancing of node load is one of the major task. In this paper, we have used switching algorithm to switch the nodes to balance the node load which further increases the life time of each node by finding the shortest path to destination from the source node based on the threshold energy. Further we applied base localization algorithm to check the lifetime of each node.

scholarly journals Integrated Earthquake and Landslide Monitoring Over Wireless Sensor Network

2019 ◽  
Vol 8 (4) ◽  
pp. 9594-9599
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Warning System ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Landslide Monitoring ◽  
Processing Unit ◽  
Time Data ◽  
Moisture Sensor ◽  
The Impact

Natural disasters have mercilessly devastated our lives in so many different terms. The impact of Earthquake and landslides are very severe because of their unpredictability. To alleviate the problem early warning system plays an important role. In this paper, we proposed an integrated earthquake and landslide monitoring system overthewireless sensor network. The Wireless Sensor Network is programmed to acquire the data, which is monitored and controlled centrally or independently and can be distributed widely in a random or planned deployment. By detecting suspicious indications such as tremor or landslides through sensor nodes, the system provides information to the monitoring and warning station. The processing unit is composed of arduino and Sensors such as 4.5 Flex Sensor, Capacitive Soil Moisture Sensor and a3-Dimensional Accelerometer are used in the proposed system to monitor landmass displacement/movement, the moisture level of the soil and the vibrations for earthquakes respectively. An RF module, XBee S2C is used which provides wireless communication with a range of about a 1 km line of sight and 60 meters indoor. The real-time data can be accessed via the internet. It will be powered from a 12V 20W solar panel with rechargeable Li-Ion Battery and fitted with necessary protection and charging circuit boards. The proposed system can be used in earthquake and landslide prone area to avoid damages to life and property in the area of operation by providing crucial information and further warning for any disastrous development. The proposed system is implemented through experiments and proved to be effective

WSN Localization Algorithm Based on Fast SVM

2013 ◽  
Vol 433-435 ◽  
pp. 750-753 ◽  
Author(s):  
Fang Zhu ◽  
Jun Fang Wei
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Experimental Results ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Error ◽  
Localization Algorithm ◽  
Svm Algorithm

Localization of sensor nodes is essential for wireless sensor network when it is applied to the special applications.This paper proposed a rang-free localization algorithm based on SVM. In this algorithm, multi-class SVMs are applied. So to improve the performance, a fast SVM algorithm is proposed in this paper.Finally, the experimental results demonstrate the algorithm proposed has small localization error, and it is robust and stable.

The Impact of Incapacitation of Multiple Critical Sensor Nodes on Wireless Sensor Network Lifetime

2017 ◽  
Vol 6 (3) ◽  
pp. 306-309 ◽  
Author(s):  
Huseyin Ugur Yildiz ◽  
Bulent Tavli ◽  
Behnam Ojaghi Kahjogh ◽  
Erdogan Dogdu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
The Impact

scholarly journals Analysis of AODV protocol under sinkhole attack in wireless sensor network

2018 ◽  
Vol 7 (2.4) ◽  
pp. 153
Author(s):  
Harkesh Sehrawat ◽  
Yudhvir Singh ◽  
Vikas Siwach
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Security Attacks ◽  
Aodv Protocol ◽  
The Impact

A Wireless Sensor Network (WSNs) is a collection of number of sensor nodes which are left open in an unsecured environment. Sensor nodes work and communicate together to attain the desired goals. They are placed at the locations where monitoring is otherwise impossible. Wireless Sensor Networks are resource constrained which may be computational power, memory capacity, battery power etc. As Wireless Sensor Networks are implemented in the unattended environment, they are prone to discrete type of security attacks. Because of their limitations these networks are easily targeted by intruders. Sinkhole attack is one of the security attacks which try to disturb the ongoing communication in wireless sensor network. In sinkhole attack, the intruder or the malicious node try to attract the network traffic towards itself, that sensor nodes will pass data packets through this compromised node thereby manipulating messages which sensor nodes are transferring to the base station. In this paper we analyze the impact of Sinkhole attack on AODV protocol under various conditions. We analyzed the impact of Sinkhole attack on AODV protocol with varying number of attacker nodes.  

scholarly journals Wireless Sensor Network Dynamic Mathematics Modeling and Node Localization

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Xiaoyang Liu ◽  
Chao Liu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Rapid Development ◽  
Location Estimation ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Dynamic ◽  
Localization Algorithm ◽  
Node Localization ◽  
Dynamic Mathematics

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.

scholarly journals Localization in Wireless Sensor Network Using MDS

2012 ◽  
pp. 228-233
Author(s):  
Rashmi Agrawal ◽  
Brajesh Patel
Keyword(s):  
Wireless Sensor Network ◽  
Multidimensional Scaling ◽  
Sensor Network ◽  
Complex Terrain ◽  
Estimation Method ◽  
Position Estimation ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Sensor Positioning

In this paper, determining the localization of nodes in a Wireless Sensor Network is a very important task, which involves collaboration between sensor nodes. Localization is a fundamental service since it is relevant to many applications and to the network main functions, such as: routing, communication, cluster creation, network coverage, etc. Collaboration is essential to self-localization, so that localization can be accomplished by the nodes themselves, without any human intervention. In this paper, we first analyze the key aspects that have to be considered when designing or choosing a solution for the localization problem. Then, we present MDS localization algorithm. With this analysis of results simulated. We identified the results in topologies by taking different cases and we have addresses shortcomings, which are caused by anisotropic network topology and complex terrain, of existing sensor positioning methods. Then, we explore the idea of using multidimensional scaling technique to compute relative positions of sensors in a wireless sensor network. A distributed sensor positioning method based on multidimensional scaling is proposed to get the accurate position estimation and reduce error cumulation. Comparing with other positioning methods, with very few anchors, our approach can accurately estimate the sensors’ positions in network with anisotropic topology and complex terrain as well as eliminate measurement error cumulation. We also propose an on demand position estimation method based on multidimensional scaling for one or several adjacent sensors positioning. Experimental results indicate that our distributed method for sensor position estimation is very effective and efficient.

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