An Enhanced technique of Self-Correcting Localization Algorithm for Vehicular Node Position Accuracy in the Distributed VANET

One of the main issues of wireless sensor networks is localization. Besides, it is important to track and analyze the sensed information. The technique of localization can calculate node position with the help of a set of designed nodes, denoted as anchors. The set density of these anchors may be incremented or decremented because of many reasons such as maintenance, lifetime, and breakdown. The well-known Distance Vector Hop (DV-Hop) algorithm is a suitable solution for localizing nodes having few neighbor anchors. However, existing DV-Hop-based localization methods have not considered the problem of anchor breakdown which may happen during the localization process. In order to avoid this issue, an Online Sequential DV-Hop algorithm is proposed in this paper to sequentially calculate positions of nodes and improve accuracy of node localization for multihop wireless sensor networks. The algorithm deals with the variation of the number of available anchors in the network. We note that DV-Hop algorithm is used in this article to process localization of nodes by a new optimized method for the estimation of the average distance of hops between nodes. Our proposed localization method is based on an online sequential computation. Compared with the original DV-Hop and other localization methods from the literature, simulation results prove that the proposed algorithm greatly minimizes the average of localization error of sensor nodes.

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A Localization Method for WSN Based on Variable Transmission Power

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.694-697.1055 ◽

2013 ◽

Vol 694-697 ◽

pp. 1055-1059

Author(s):

Guang Xiong Huang ◽

Zhi Long Shan

Keyword(s):

Wireless Sensor Network ◽

Wireless Sensor ◽

Location Information ◽

Transmission Power ◽

Localization Algorithm ◽

Localization Method ◽

Position Accuracy ◽

Variable Transmission ◽

Simulation Results ◽

Range Free

Localization is an essential technology in the application of wireless sensor network. As a range-free localization algorithm, DV-Hop works well in dense and isotropic networks, but not much in irregular and sparse topologies, especially in the big curvature of shortest path case. In this paper, location information beyond the communication range was obtained by means of variable transmission power of enhanced nodes. Besides, three schemes was proposed to meet the need of different scenarios. Moreover, the simulation results validate that our method can improve position accuracy about 20% and ameliorate the performance of DV-Hop in irregular scenario.

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Research on an Improved Self-Correcting Location Algorithm for Wireless Local Region

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.128-129.1325 ◽

2011 ◽

Vol 128-129 ◽

pp. 1325-1328

Author(s):

Zheng Zhang ◽

Min Jiang ◽

Guo Cheng Wan ◽

Xiao Wei Liu

Keyword(s):

Local Region ◽

Wireless Sensor ◽

Main Function ◽

Test Results ◽

Localization Algorithm ◽

Back Testing ◽

Ranging Error ◽

Exact Position ◽

Location Algorithm ◽

Node Position

Node position technology is an internal demand of wireless sensor network, however, in most project account; it’s hard to obtain the nodes' exact position because of uncontrollability in the network deployment process. For this purpose, an improved self-correcting location algorithm which based on RSSI multilateral ranging was proposed in this paper. Other than the primary multilateral localization algorithm, a correcting node which adjacent to the blind node was imported into the pending location region. The main function is to reduce the influence caused by unilateral ranging error in the calculation of multilateral positioning and improves the positioning precision. Detailedly introduced the principle of self-correcting location algorithm, moreover, in order to check the improved algorithm’s location performance, a back testing was done via CC2430/CC2431 wireless nodes. Test results show that improved algorithm enhances the system’s accuracy and stability.

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Localization of Cooperative WSN using Distributed PSO with Optimum References

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v6i6.pp3094-3102 ◽

2016 ◽

Vol 6 (6) ◽

pp. 3094

Author(s):

Ravichander Janapati ◽

Ch. Balaswamy ◽

K. Soundararajan

Keyword(s):

Indoor Environment ◽

Pso Algorithm ◽

High Accuracy ◽

Position Accuracy ◽

Optimum Selection ◽

Anchor Nodes ◽

Accurate Position ◽

Node Position ◽

Selection Of

<p>In indoor environment WSN nodes are deployed randomly and do not know the accurate position. Find the node position with the help of anchor nodes is known as localization. CRB algorithm selects the best anchor nodes which gives high accuracy. In this paper distributed PSO algorithm with optimum selection of reference nodes using CRB is proposed to find accurate node position. The proposed method performs better in comparison with other algorithms like PSO, RLS, LMS and GPS in terms of position accuracy, latency and complexity.</p>

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Localization Technology Based on Quantum-Behaved Particle Swarm Optimization Algorithm for Wireless Sensor Network

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.220-223.1852 ◽

2012 ◽

Vol 220-223 ◽

pp. 1852-1856 ◽

Cited By ~ 1

Author(s):

Ji Zhao ◽

Yi Fu ◽

Han Bo Wang

Keyword(s):

Particle Swarm Optimization ◽

Optimization Algorithm ◽

Particle Swarm Optimization Algorithm ◽

Particle Swarm ◽

Pso Algorithm ◽

Wireless Sensor ◽

Node Localization ◽

Swarm Optimization ◽

Position Accuracy ◽

Node Position

This paper proposed a distributed iterative localization technology of wireless sensor networks (WSNs) to solve the problem of node localization. In this approch, once the nodes get localized, they act as references for the rest of nodes to localize. The ranging-based localization problem is formulated as a multidimensional optimization issue, and the quantum-behaved particle swarm optimization algorithm (QPSO) is used to exploit their quick convergence to quality solutions. Finally, the simulation results compared with the particle swarm optimization algorithm (PSO) algorithm show that QPSO outperforms the PSO and improve the node position accuracy, which prove the validity of the presented method.

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Localization of Cooperative WSN using Distributed PSO with Optimum References

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v6i6.11427 ◽

2016 ◽

Vol 6 (6) ◽

pp. 3094

Author(s):

Ravichander Janapati ◽

Ch. Balaswamy ◽

K. Soundararajan

Keyword(s):

Indoor Environment ◽

Pso Algorithm ◽

High Accuracy ◽

Position Accuracy ◽

Optimum Selection ◽

Anchor Nodes ◽

Accurate Position ◽

Node Position ◽

Selection Of

<p>In indoor environment WSN nodes are deployed randomly and do not know the accurate position. Find the node position with the help of anchor nodes is known as localization. CRB algorithm selects the best anchor nodes which gives high accuracy. In this paper distributed PSO algorithm with optimum selection of reference nodes using CRB is proposed to find accurate node position. The proposed method performs better in comparison with other algorithms like PSO, RLS, LMS and GPS in terms of position accuracy, latency and complexity.</p>

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ZigBee Node Locating Technology Based on Genetic Algorithm

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.225-226.70 ◽

2011 ◽

Vol 225-226 ◽

pp. 70-74

Author(s):

Tie Zhou Wu ◽

Hui Jun Zhou ◽

Biao Li ◽

Qing Xiao

Keyword(s):

Genetic Algorithm ◽

Measurement Data ◽

Least Square Method ◽

Least Square ◽

Wireless Sensor ◽

Localization Algorithm ◽

Position Accuracy ◽

The Common ◽

Modified Algorithm ◽

Step Localization

Location technology as Wireless Sensor Network’s support technology for most applications has been widely researched, ZigBee is one of representative technology of WSN. On the basis of the common two-step localization algorithm, this paper proposes a locating method that optimize the measurement data using genetic algorithm before locating calculation, then using multilateral measurement least-square method for calculating position. Experimental results show that the modified algorithm is significantly reduced the position error, effectively improve the position accuracy.

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A Wireless Sensor Network Localization Method Based on Dynamic Path Loss Exponent

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.433-440.4530 ◽

2012 ◽

Vol 433-440 ◽

pp. 4530-4535

Author(s):

Gang Zhu Qiao ◽

Jian Chao Zeng

Keyword(s):

Path Loss ◽

Space Environment ◽

Communication Model ◽

Localization Algorithm ◽

Network Localization ◽

Path Loss Exponent ◽

Rf Signals ◽

Wireless Signal ◽

Location Algorithm ◽

Node Position

The path loss exponent shows the effect of space environment on the RF signals in wireless communication model. In most RSSI based location method the path loss exponent is assigned a fixed empirical value which can not reflect the actual environmental impact of the wireless signal, which lead to low position accuracy and considerable positioning error. Aiming at some complex and rapidly changing environment a path loss exponent dynamic acquired algorithm is proposed, which can calculate the actual path loss exponent with the distance and the RSSI value information between adjacent beacon nodes. On basis of the path loss exponent dynamic acquired algorithm a path loss exponent dynamic acquired based localization algorithm is proposed which can estimate the blind node position with the actual path loss exponent, and can improve the adaptability to the environment of the RSSI location algorithm. The simulation shows that the positioning accuracy of proposed method is significantly improved and the effect of proposed method is more precise than the common RSSI method under the same environment.

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