Retracted: A Three-Dimensional DV-Hop Localization Algorithm Based on RSSI

Gou, Pingzhang; Li, Fengzhen; Jia, Xiangdong; Mao, Gang; Sun, Mengyuan

doi:10.1109/icscse.2018.00179

Cited by 6 publications

(3 citation statements)

References 5 publications

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“…Range-based scheme demonstrated superior performance in location accuracy, so, several scholars applied it in DV-Hop algorithm. Received signal strength indicator (RSSI) [38] is utilized to calculate weighted factor based on its first order partial derivative by Gou et al [39]. AHS and estimate distance to unknown nodes are enhanced by above mentioned weighted factor.…”

Section: Based On Hybrid Localization Algorithmmentioning

confidence: 99%

A Survey on DV-Hop localization Techniques in Three- Dimensional Wireless Sensor Networks

et al. 2020

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Location information is prerequisite for wireless sensor networks (WSNs) monitoring and control applications, since there is no meaning without position information for collected data. Distance vector hop (DV-Hop) localization algorithm as the typical range-free algorithm that has been widely applied in various applications. Nowadays, the research on range-free localization for WSNs is mostly based on two-dimensional (2D) space. Hence, there are few surveys concentrated on range-free localization in three-dimensional (3D) WSNs. This motivated us to present an extensive overview of enhanced DV-Hop localization algorithms in 3D WSNs. This paper focused on critical challenge between 2D and 3D in localization model, representative range-free 3D localization technique surveys. Moreover, a comprehensive taxonomy of most essential enhanced methods applied in 3D DV-Hop is illustrated. A considerable comparison in term of localization error, computational complexity and node type is given. Future research directions dealing with localization under 3D DV-Hop is also discussed.

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Section: Based On Hybrid Localization Algorithmmentioning

confidence: 99%

A Survey on DV-Hop localization Techniques in Three- Dimensional Wireless Sensor Networks

et al. 2020

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“…In the field of research, the most used range-free techniques include APIT [5], Centroid [6],Distance Vector-Hop (DVHOP) [7,8,9] and Amorphous [10] algorithm. On the other hand, range-based techniques [11] make the localization by using Time of Arrival (TOA) [12], Angle of Arrival(AOA) [13], Time Difference Of Arrival (TDOA) [14] and Received Signal Strength Indicator(RSSI) [15]. In general, those methods require extra material but they offer a high level of accuracy, making them more precise and expensive than range-free techniques.…”

Section: Introductionmentioning

confidence: 99%

A new approach for DVHOP localization algorithm improvement in Wireless Sensor Network

Arroub,

Darif,

Saadane

et al. 2023

Preprint

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Wireless sensor networks (WSN) are mostly utilized in many applications. Indeed, WSN is composed of sensors to evaluate some physical phenomena. However, the information brought by the sensor still missed if we don't know the exact location of the event. Several localization algorithms have been proposed in order to locate the nodes in WSN. The localization algorithms are categorized into range-based and range-free techniques. The range-based techniques use either distance or time to calculate the coordinates of unknown nodes. Nevertheless, those kinds of techniques need some additional material in computation purpose. Therefore, range-based techniques present an expensive solution for positioning in WSN. Alternatively, range-free techniques may do the same task without involving additional material. But they don’t offer a high precision of localization in comparison with range-based techniques. DVHOP is the most popular range-free technique that uses the hop count method in the localization process. In this work, we propose an improvement of DVHOP localization algorithm to create three improved versions of this algorithm and we have achieved that by adopting two meta-heuristic (simulated annealing, particle swarm optimization) and FMINCON solver dedicated to the optimization in the field of WSN nodes localization. The experimental results obtained in this work show clearly the gain and the good impact of our proposition.

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“…The direct-ranging-method utilizes additional hardware to measure the angle, distance and signal strength between nodes, and then calculates the localization information of the nodes by using the obtained data [ 11 ]. Typical direct-ranging-methods include strength indication of received signal (RSSI) [ 12 , 13 ], time difference of arrival (TDOA) [ 14 ], time of arrival (TOA) [ 15 , 16 ], angle of arrival (AOA) [ 17 , 18 ], and so forth. Indirect-ranging-method mainly uses geometric relationship between nodes, hop-count value and energy loss between nodes, network connectivity and other aspects to estimate the location of unknown nodes [ 19 ].…”

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

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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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Retracted: A Three-Dimensional DV-Hop Localization Algorithm Based on RSSI

Cited by 6 publications

References 5 publications

A Survey on DV-Hop localization Techniques in Three- Dimensional Wireless Sensor Networks

A Survey on DV-Hop localization Techniques in Three- Dimensional Wireless Sensor Networks

A new approach for DVHOP localization algorithm improvement in Wireless Sensor Network

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

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