CRWSNP: cooperative range-free wireless sensor network positioning algorithm

Darakeh, Fatemeh; Mohammad-Khani, Gholam Reza; Azmi, Paeiz

doi:10.1007/s11276-017-1505-2

Cited by 12 publications

(5 citation statements)

References 41 publications

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“…The so-called sensor device refers to a device that integrates wireless communication capabilities, embedded computing capabilities, perception capabilities, and storage capabilities. These devices can perform simple monitoring tasks and information processing tasks, and a large number of sensor nodes are combined to form a wireless sensor network [18]. At present, wireless Mesh networks have been widely used in the formation of Internet networks such as home networks and community networks, such as common WIFI mesh networks and campus wireless networks.…”

Section: Wireless Sensor Networkmentioning

confidence: 99%

RETRACTED ARTICLE: Evaluation of the value of basketball players based on wireless network and improved Bayesian algorithm

Dong

2020

J Wireless Com Network

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The selection of basketball players should highlight their specific characteristics and proceed according to the essential laws of basketball. When the acquired training level becomes closer and closer, and is more and more conducive to the control of the entire training and competition, the selection of the standard paradigm of basketball players plays a key role. At present, the existing evaluation methods of basketball players are limited to the human experience of coaches, and there is a lack of further information evaluation methods. This article discusses a new type of basketball player evaluation scheme that combines wireless network and machine learning methods. First, the wireless sensor network is used to perceive basketball players' performance on the court and record various evaluation indicators. Secondly, establish a player value evaluation model through improved Bayesian algorithm and fuzzy comprehensive evaluation methods. Finally, after relevant tests and comparisons with the coaches' results, the model showed better evaluation results and a fairer value distribution.

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Section: Wireless Sensor Networkmentioning

confidence: 99%

RETRACTED ARTICLE: Evaluation of the value of basketball players based on wireless network and improved Bayesian algorithm

Dong

2020

J Wireless Com Network

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“…This method needs extra hardware and therefore increases the cost and power consumption. Moreover, Darakeh et al [13] introduced the DCRL-WSN localization method which defines a ball-shaped extended bound for each node and takes advantage of the certainty rule for reducing this area.…”

Section: Related Workmentioning

confidence: 99%

“…Then, a bounding box zone is estimated for every node (the unknown node) based on the radio radius of the anchor and extended bounds of the nodes by evaluating two constrained convex optimization problems. Additionally, Darakeh et al [13] attempted to calculate the initial node position using convex optimization and then enhance the position of the nodes by two novel heuristic techniques for location correction. These two methods need plenty of anchor nodes to estimate the position and thus increase the cost and power consumption increment.…”

Section: Related Workmentioning

confidence: 99%

“…In contrast, range-based methods use several approaches to calculate the distance or angle among nodes in order to estimate the location of each node. These techniques include the Time of Arrival ToA) [10], Time Difference of Arrival (TDoA) [11][12], Received Signal Strength Indicator (RSSI) [13], techniques for calculating distance and the Angle of Arrival of the signal (AoA) [14], technique for calculating angle ,and also hybrid methods that are combination of the abovementioned techniques [15], [16]. The present study focuses on random deployment of static sensor nodes which used one mobile anchor node as a reference node to calculate the nodes positions in network area.…”

Section: Introductionmentioning

confidence: 99%

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Low Power Fast and Accurate Localization Algorithm in Wireless Sensor Networks

Sharma¹,

Kharub²

2021

CVRJST

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Finding precise node localization is one of the critical issues in wireless sensor networks (WSNs), as the nodes are generally deployed randomly in the area of interest and without location stamp of the event, there is no use of that particular information. In this paper, a range-free localization algorithm called Horizontal-Vertical (H-V) scan method is presented which works mainly on collinearity concept. This method firstly estimates the collinearity of anchor nodes and rules out those anchor nodes which are collinear for location estimation of target nodes. By ruling out collinear anchor nodes, location is calculated by other than these ruled out anchor nodes through trilateration method which improves the localization accuracy. A new trajectory is also proposed for this method which improves coverage, accuracy and time for calculating localization. Simulation results show that the proposed method performs better in terms of localization accuracy, than the existing similar range-free localization methods.

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“…This algorithm used DV-Hop to re-estimate beacon node position to obtain error, and then used the optimal algorithm to find the optimal value of hop distance to improve the positioning accuracy. Reference [11] proposed to use convex programming to find the location estimation of the nodes to be located, and then cooperated with the nodes in several iterations to improve the location estimation of all the nodes to be measured. Compared with the APIT algorithm, it had more accurate location results.…”

Section: Introductionmentioning

confidence: 99%

Research of localization algorithm for wireless sensor network based on DV-Hop

Xue

2019

J Wireless Com Network

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Wireless sensor network (WSN) possesses very broad application prospect in many fields, where the node location technology is one of the key technologies of WSN. Distance vector hop (DV-Hop) localization algorithm is a widely used algorithm in this technology, and it uses routing exchange protocol to make unknown nodes obtain beacon node information which will be used for coordinate calculation, therefore there exists certain error for the algorithm itself. Aiming at the disadvantage of large error existing in the traditional wireless sensor network location algorithm based on DV-Hop, an improved DV-Hop algorithm based on hop thinning and distance correction is proposed. The minimum hop is corrected by introducing received signal strength indication (RSSI) ranging technology, and the average hop distance is corrected by weighted average value of hop distance error and estimated distance error. Subsequently, the overall improvement on the location performance of the Hop-DV location algorithm is realized, and the location error is reduced. Under the Matlab simulation environment, the simulation experiment on the improved algorithm is carried out. The experimental results show that the improved algorithm reduces the location error and has higher location accuracy.

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CRWSNP: cooperative range-free wireless sensor network positioning algorithm

Cited by 12 publications

References 41 publications

RETRACTED ARTICLE: Evaluation of the value of basketball players based on wireless network and improved Bayesian algorithm

RETRACTED ARTICLE: Evaluation of the value of basketball players based on wireless network and improved Bayesian algorithm

Low Power Fast and Accurate Localization Algorithm in Wireless Sensor Networks

Research of localization algorithm for wireless sensor network based on DV-Hop

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