Localization System Optimization in Wireless Sensor Networks (LSO-WSN)

2020 ◽  
pp. 1048-1081
Author(s):  
Surjit Singh ◽  
Rajeev Mohan Sharma
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
System Optimization ◽  
Wireless Sensor ◽  
Computational Techniques ◽  
Computational Technique ◽  
Node Localization ◽  
Position Information ◽  
Localization System ◽  
Node Location

Localization of nodes in wireless sensor networks is needed to track/know the event origin and node location both, routing, network coverage and querying of sensor clusters. Wireless Sensor Networks (WSN) have different applications along with different challenges. Here, position information system is one of the challenging aspect that plays an important role in increasing the lifetime and survivability of WSN. And, the computational techniques have been successfully used in recent years to address the localization system of nodes in WSN. However it is very difficult to know about the best computational technique for optimizing localization system of nodes. This work intends to close the gap for selecting suitable computational technique for node localization system optimization. Our aim is to provide a better understanding of the current research trends in this field.

Localization System Optimization in Wireless Sensor Networks (LSO-WSN)

2017 ◽  
pp. 1-34 ◽  
Author(s):  
Surjit Singh ◽  
Rajeev Mohan Sharma
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
System Optimization ◽  
Wireless Sensor ◽  
Computational Techniques ◽  
Computational Technique ◽  
Node Localization ◽  
Position Information ◽  
Localization System ◽  
Node Location

Localization of nodes in wireless sensor networks is needed to track/know the event origin and node location both, routing, network coverage and querying of sensor clusters. Wireless Sensor Networks (WSN) have different applications along with different challenges. Here, position information system is one of the challenging aspect that plays an important role in increasing the lifetime and survivability of WSN. And, the computational techniques have been successfully used in recent years to address the localization system of nodes in WSN. However it is very difficult to know about the best computational technique for optimizing localization system of nodes. This work intends to close the gap for selecting suitable computational technique for node localization system optimization. Our aim is to provide a better understanding of the current research trends in this field.

A Localization Algorithm of Nodes Based on Hypersphere Granular Computing in Wireless Sensor Networks

2014 ◽  
Vol 998-999 ◽  
pp. 1390-1393
Author(s):  
Yong He
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Training Set ◽  
Node Localization ◽  
Single Output ◽  
Node Location ◽  
Unknown Node

This paper proposes a node localization algorithm based on super chondritic calculation, super chondritic calculation scanning of a training set is able to complete the training process, the training has characteristics of fast, the problem of node localization for wireless sensor networks. Firstly, according to the related parameter information for the location of wireless sensor nodes, a multi input, multi output problem of training set, and then through the methods of grid division, location area, the original training set into the classification of multi input, single output training set, the super chondritic algorithm by scanning training, in order to get the relevant parameters, and the estimation of the unknown node location. Simulation results show that the proposed algorithm has better positioning accuracy.

scholarly journals An improved node localization algorithm based on DV-Hop for wireless sensor networks

2011 ◽  
Vol 8 (4) ◽  
pp. 953-972 ◽  
Author(s):  
Qingji Qian ◽  
Xuanjing Shen ◽  
Haipeng Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Location Error ◽  
Node Localization ◽  
Localization Algorithms ◽  
Node Location ◽  
The Impact

Sensor node localization is the basis for the entire wireless sensor networks. Because of restricted energy of the sensor nodes, the location error, costs of communication and computation should be considered in localization algorithms. DV-Hop localization algorithm is a typical positioning algorithm that has nothing to do with distance. In the isotropic dense network, DV-Hop can achieve position more precisely, but in the random distribution network, the node location error is great. This paper summed up the main causes of error based on the analysis on the process of the DV-Hop algorithm, aimed at the impact to the location error which is brought by the anchor nodes of different position and different quantity, a novel localization algorithm called NDVHop_Bon (New DV-Hop based on optimal nodes) was put forward based on optimal nodes, and it was simulated on Matlab. The results show that the new proposed location algorithm has a higher accuracy on localization with a smaller communication radius in the circumstances, and it has a wider range of applications.

Privacy Intensity Policy for Optimizing Source Node Location in Wireless Sensor Networks

2020 ◽  
Vol 57 (24) ◽  
pp. 241017
Author(s):  
蒋占军 Jiang Zhanjun ◽  
周涛 Zhou Tao ◽  
杨永红 Yang Yonghong
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Source Node ◽  
Wireless Sensor ◽  
Node Location

scholarly journals Localization by Salp Swarm Optimization with Doppler Effect in Wireless Sensor Networks

2021 ◽  
Vol 13 (6) ◽  
pp. 26-40
Author(s):  
Panimalar Kathiroli ◽  
◽  
Kanmani. x Kanmani. S
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Doppler Effect ◽  
Computation Time ◽  
Wireless Sensor ◽  
Multidimensional Space ◽  
Node Localization ◽  
Swarm Optimization ◽  
Localization Model ◽  
Random Node

Wireless sensor networks (WSNs) have lately been widely used due to its abundant practice in methods that have to be spread over a large range. In any wireless application, the position precision of node is an important core component. Node localization intends to calculate the geographical coordinates of unknown nodes by the assistance of known nodes. In a multidimensional space, node localization is well-thought-out as an optimization problem that can be solved by relying on any metaheuristic’s algorithms for optimal outputs. This paper presents a new localization model using Salp Swarm optimization Algorithm with Doppler Effect (LOSSADE) that exploit the strengths of both methods. The Doppler effect iteratively considers distance between the nodes to determine the position of the nodes. The location of the salp leader and the prey will get updated using the Doppler shift. The performance validation of the presented approach simulated by MATLAB in the network environment with random node deployment. A detailed experimental analysis takes place and the results are investigated under a varying number of anchor nodes, and transmission range in the given search area. The obtained simulation results are compared over the traditional algorithm along with other the state-of-the-art methods shows that the proposed LOSSADE model depicts better localization performance in terms of robustness, accuracy in locating target node position and computation time.

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