Distance Error Correction Based Hop Localization Algorithm for Wireless Sensor Network

Prashar, Deepak; Jyoti, Kiran

doi:10.1007/s11277-019-06225-0

Cited by 17 publications

(20 citation statements)

References 40 publications

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“…6 shows that the proposed algorithm performed better than the other four algorithms. Its average localization error decreased to 70%, 55%, 50%, and 53%, when compared with the algorithm prescribed in [10,15,18,32], respectively. As portrayed in Fig.…”

Section: ) Effect Of Total Number Of Nodesmentioning

confidence: 91%

“…The ICA-DV-hop resulted in the highest localization accuracy among the three algorithms. Deepak et al [32] introduced a new metric-based method, in which the author proved that it gave less errors, when compared to the conventional DV-Hop using mathematical analysis.…”

Section: Related Workmentioning

confidence: 99%

“…In verifying the performance of WND-DV-Hop, comprehensive experiments were conducted in MATLAB 2016a. The experimental outcomes were compared with DV-Hop [10], IDV-Hop [15], CheckOut-DV-Hop [18], and New-IDV-Hop [32] in simulated settings. Table I tabulates the simulation parameters.…”

Section: A Experimental Environmentmentioning

confidence: 99%

“…5 presents the LE for each unknown node under five algorithms. Apparently, the proposed algorithm (WND-DV-Hop) gave the best outcomes with reduction in localization error at 55%, 35%, 20%, and 25%, respectively, compared with DV-Hop [10], IDV-Hop [15], CheckOut-DV-Hop [18], and New-IDV-Hop [32].…”

Section: • Le For Each Unknown Nodementioning

confidence: 99%

See 3 more Smart Citations

An Enhanced Distance Vector-Hop Algorithm using New Weighted Location Method for Wireless Sensor Networks

Han¹,

Mohamed²,

Liu³

et al. 2020

IJACSA

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Location is an indispensable segment for WirelessSensor Network (WSN), since when events happened, we need to know location. The distance vector-hop (DV-Hop) technique is a popular range-free localization algorithm due to its cost efficiency and non-intricate process. Nevertheless, it suffers from poor accuracy, and it is highly influenced by network topology; Especially, more hop counts lead to more errors. In the final phase, least squares are employed to address nonlinear equation, which will gain greater location errors. Aimed at addressing problems mentioned above, an enhanced DV-Hop algorithm based on weighted factor, along with new weighted least squares location technique, is proposed in this paper, and it is called WND-DV-Hop. First, the one hop count of unknown node was corrected by employed received signal strength indication (RSSI) technology. Next, in order to reduce average hop distance error, a weighted coefficient based on beacon node hop count was constructed. A new weighted least squares method was embedded to solve nonlinear equation problem. Finally, considerable experiments were carried out to estimate the performance of WND-DV-Hop, compared the outcomes with state-of-the-art DV-Hop, IDV-Hop, Checkout-DV-Hop, and New-DV-Hop depicted in literature. The empirical findings demonstrated that WND-DV-Hop significantly outperformed other localization algorithms.

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Section: ) Effect Of Total Number Of Nodesmentioning

confidence: 91%

Section: Related Workmentioning

confidence: 99%

Section: A Experimental Environmentmentioning

confidence: 99%

Section: • Le For Each Unknown Nodementioning

confidence: 99%

See 2 more Smart Citations

An Enhanced Distance Vector-Hop Algorithm using New Weighted Location Method for Wireless Sensor Networks

Han¹,

Mohamed²,

Liu³

et al. 2020

IJACSA

View full text Add to dashboard Cite

show abstract

“…In recent years, many scholars have conducted in-depth research on the DV-Hop algorithm and proposed different improved methods for the shortcomings of the algorithm, all of which have improved the positioning accuracy and performance of the algorithm. The existing DV-Hop algorithm is mainly improved from the following four aspects: optimizing the average hop distance or minimum hop number, selecting the optimal beacon node, and optimizing the location calculation method [17][18][19][20][21][22][23][24]. In literature [25], the teaching-learning-based optimization (TLBO) algorithm was adopted to improve the DV-Hop.…”

Section: Related Workmentioning

confidence: 99%

An improved range-free location algorithm for industrial wireless sensor networks

Wang

Liu

et al. 2020

J Wireless Com Network

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In the traditional DV-Hop location algorithm, the number of hops within the communication radius is counted as one hop. However, in the case of uneven distribution of nodes, this method will bring a large error to the calculation of hop distance. In order to solve the above problems, an improved DV-Hop location algorithm with multiple communication radius is proposed in this paper. Based on the multi-communication radius location algorithm, the method uses the cosine theorem to correct the hop number and estimated the average hop distance, and optimizes the estimated distance of the unknown node. The algorithm uses multiple communication radius to broadcast the position to obtain the minimum number of hops between the unknown node and the beacon node and adjusts the estimated hop distance by using the cosine theorem after estimating the good hop distance, and finally uses the trilateration method, or the maximum likelihood estimation method estimates the position coordinates. The experimental results show that compared with the traditional DV-Hop algorithm and DDV-Hop algorithm, the improved DV-Hop algorithm improves the positioning accuracy and reduces the average positioning error of the unknown nodes.

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Optimization of WSN localization algorithm based on improved multi-strategy seagull algorithm

Yu,

Liu,

Liu

2024

Telecommun Syst

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Distance Error Correction Based Hop Localization Algorithm for Wireless Sensor Network

Cited by 17 publications

References 40 publications

An Enhanced Distance Vector-Hop Algorithm using New Weighted Location Method for Wireless Sensor Networks

An Enhanced Distance Vector-Hop Algorithm using New Weighted Location Method for Wireless Sensor Networks

An improved range-free location algorithm for industrial wireless sensor networks

Optimization of WSN localization algorithm based on improved multi-strategy seagull algorithm

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