Improvement of DV-Hop localization algorithm for randomly deployed wireless sensor networks

Messous, Salma; Liouane, Hend; Liouane, Noureddine

doi:10.1007/s11235-019-00592-6

Cited by 40 publications

(49 citation statements)

References 27 publications

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“…DV-Hop algorithm is simple, widely used, stable and easy to expand [ 26 ]. Many researchers put forward different ideas to enhance the localization accuracy of the algorithm: Tang et al used TDOA location feature to quantify the hop value of nodes in DV-Hop location algorithm to achieve a stable effect [ 32 ].…”

Section: Related Workmentioning

confidence: 99%

“…In different networks, its localization results are relatively accurate and reasonable, and the network robustness is also strong [ 25 ]. However, there is a large localization error in the random sensor networks with uneven density [ 26 ]. The larger the minimum hop-count value from the localization node to the beacon node, the greater the cumulative error value [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

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Three-Dimensional Localization Algorithm Based on Improved A* and DV-Hop Algorithms in Wireless Sensor Network

Huang

Han

Cui

et al. 2021

Sensors

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In the traditional wireless sensor networks (WSNs) localization algorithm based on the Internet of Things (IoT), the distance vector hop (DV-Hop) localization algorithm has the disadvantages of large deviation and low accuracy in three-dimensional (3D) space. Based on the 3DDV-Hop algorithm and combined with the idea of A* algorithm, this paper proposes a wireless sensor network node location algorithm (MA*-3DDV-Hop) that integrates the improved A* algorithm and the 3DDV-Hop algorithm. In MA*-3DDV-Hop, firstly, the hop-count value of nodes is optimized and the error of average distance per hop is corrected. Then, the multi-objective optimization non dominated sorting genetic algorithm (NSGA-II) is adopted to optimize the coordinates locally. After selection, crossover, mutation, the Pareto optimal solution is obtained, which overcomes the problems of premature convergence and poor convergence of existing algorithms. Moreover, it reduces the error of coordinate calculation and raises the localization accuracy of wireless sensor network nodes. For three different multi-peak random scenes, simulation results show that MA*-3DDV-Hop algorithm has better robustness and higher localization accuracy than the 3DDV-Hop, PSO-3DDV-Hop, GA-3DDV-Hop, and N2-3DDV-Hop.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Localization Algorithm Based on Improved A* and DV-Hop Algorithms in Wireless Sensor Network

Huang

Han

Cui

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…This approach has a better effect on the average location error and improves location accuracy. Improvised DV-Hop localization algorithm proposed by M. San a, H. L i o u a n e and N. L i o u a n e [50] uses a recursive approach to locate nodes based on a collection of reference nodes selected from a predefined anchor community. This approach can be appropriate for WSNS using a multi-hop system and also achieves low localization errors.…”

Section: Angle-based Localizationmentioning

confidence: 99%

Localization in Wireless Sensor Networks: A Review

Sneha¹,

Nagarajan²

2020

Cybernetics and Information Technologies

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Wireless Sensor Network (WSN) has been a source of attraction for many researchers as well as common people for the past few years. The use of WSN in various environmental applications like monitoring of weather, temperature, humidity, military surveillance etc. is not limited. WSN is built on hundreds to thousands of nodes where each node is a sensor whose main role is to sense data. These nodes are restricted to various constraints like power, energy, efficiency and deployment. The location of deployment influences the efficiency of data transmission. In this paper we briefly discuss on localization process in WSN and the classification of localization methodologies, namely centralized localization and distributed localization. The various techniques like ToA, TDoA, AoA and RSSI that are used to estimate the distance among the nodes are studied in detail. The localization issues categorized under proximity-based, range-based and range-free localization are discussed in detail. This paper also focuses on how the nodes with GPS can contribute to the localization process. The merits and demerits of using GPS have also been looked into. The various approaches of range-based techniques like Bounding box, SumDistMinMax, geometric methods, general techniques have been discussed briefly. We will also discuss on how the factors like path loss, noise, propagation, device measurements, connectivity, power control and tracking can influence the measurements in localization. In the tracking process we have briefly discussed about the variants of Kalman filter that can be used in detecting the direct path, strongest path and undirected path. This paper as a whole is just a brush up of the localization methodologies used in wireless sensor networks. This paper may give idea to the researchers to develop efficient algorithms to localize nodes with accuracy adapting to different techniques with respect to the environment and applications to be designed.

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“…Primarily, some common range‐free methods are discussed. In [11], the authors proposed an Improved Recursive DV‐Hop localisation method to enhance the general DV‐Hop algorithm in multi‐hop networks. In this way, they utilise the polynomial approximation to optimise the average hop‐distance calculation and recursively estimate the position to improve accuracy.…”

Section: Related Workmentioning

confidence: 99%