Node localization algorithm of wireless sensor networks with mobile beacon node

Chen, Yourong; Lu, Siyi; Chen, Junjie; Ren, Tiaojuan

doi:10.1007/s12083-016-0522-8

Cited by 25 publications

(14 citation statements)

References 18 publications

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“…), a movement strategy can be chosen. Since our technique focuses on static and dynamic movement path planning, we limit our discussion only to such [ 8 , 10 , 18 , 19 , 20 , 21 , 22 , 23 ] techniques.…”

Section: Related Workmentioning

confidence: 99%

“…Considering an exceptional scenario where the MA movement is limited or constrained, the authors in [ 22 ] suggest using a multi-hop localization technique called DV-Hop to increase the localization ratio in static path planning. With a similar assumption of the limited and constrained movement, a node localization algorithm with mobile beacon node (NLA_MB) is proposed in [ 23 ]. In this model, the area of interest is divided into a number of hexagonal grids and the MA moves from the centre of the hexagon to a corner and vice versa based on the proposed optimization model to form the final movement path.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic Fuzzy-Logic Based Path Planning for Mobility-Assisted Localization in Wireless Sensor Networks

Alomari

Phillips

Aslam

et al. 2017

Sensors

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Mobile anchor path planning techniques have provided as an alternative option for node localization in wireless sensor networks (WSNs). In such context, path planning is a movement pattern where a mobile anchor node’s movement is designed in order to achieve a maximum localization ratio possible with a minimum error rate. Typically, the mobility path planning is designed in advance, which is applicable when the mobile anchor has sufficient sources of energy and time. However, when the mobility movement is restricted or limited, a dynamic path planning design is needed. This paper proposes a novel distributed range-free movement mechanism for mobility-assisted localization in WSNs when the mobile anchor’s movement is limited. The designed movement is formed in real-time pattern using a fuzzy-logic approach based on the information received from the network and the nodes’ deployment. Our proposed model, Fuzzy-Logic based Path Planning for mobile anchor-assisted Localization in WSNs (FLPPL), offers superior results in several metrics including both localization accuracy and localization ratio in comparison to other similar works.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Dynamic Fuzzy-Logic Based Path Planning for Mobility-Assisted Localization in Wireless Sensor Networks

Alomari

Phillips

Aslam

et al. 2017

Sensors

View full text Add to dashboard Cite

show abstract

“…e use of dynamic anchor node localization can greatly reduce the number of anchor nodes and can also improve the localization effect. In order to reduce the number of static anchor nodes, reduce the operation cost of the whole network, and improve the localization effect, the localization algorithm based on dynamic anchor nodes has obvious advantages [8]. Karim et al [9] proposed a range-free, energy-efficient, localization technique based on mobile anchor nodes for the large-scale machine-to-machine environment.…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Localization Algorithm of WSN Nodes Based on RSSI-TOA and Single Mobile Anchor Node

Zhang

Yang

Zhang

et al. 2019

Journal of Electrical and Computer Engineering

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Aimed at the shortcomings of low localization accuracy of the fixed multianchor method, a three-dimensional localization algorithm for wireless sensor network nodes is proposed in this paper, which combines received signal strength indicator (RSSI) and time of arrival (TOA) ranging information and single mobile anchor node. A mobile anchor node was introduced in the proposed three-dimensional localization algorithm for wireless sensor networks firstly, and the mobile anchor node moves according to the Gauss-Markov three-dimensional mobility model. en, based on the idea of using RSSI ranging in the near end and TOA ranging in the far end, a ranging method combining RSSI and TOA ranging information is proposed to obtain the precise distance between the anchor node and the unknown node. Finally, the maximum-likelihood estimation method is used to estimate the position of unknown nodes based on the obtained ranging values. e MATLAB simulation results show that the proposed algorithm had a higher localization accuracy and lower localization energy consumption compared with the traditional RSSI localization method or TOA localization method.

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“…Path planning (PP) has been fundamental in many areas in recent decades, for instance mobile robots [1][2][3], unmanned surface vehicles (USVs) [4,5], wireless sensor networks (WSNs) [6][7][8] and video games [9]. For mobile robots, path planning is devised to find one or more feasible routes from the initial location to the target in a given workspace.…”

Section: Introductionmentioning

confidence: 99%

Mobile Robot Path Planning with a Non-Dominated Sorting Genetic Algorithm

Yang

2018

Applied Sciences

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In many areas, such as mobile robots, video games and driverless vehicles, path planning has always attracted researchers’ attention. In the field of mobile robotics, the path planning problem is to plan one or more viable paths to the target location from the starting position within a given obstacle space. Evolutionary algorithms can effectively solve this problem. The non-dominated sorting genetic algorithm (NSGA-II) is currently recognized as one of the evolutionary algorithms with robust optimization capabilities and has solved various optimization problems. In this paper, NSGA-II is adopted to solve multi-objective path planning problems. Three objectives are introduced. Besides the usual selection, crossover and mutation operators, some practical operators are applied. Moreover, the parameters involved in the algorithm are studied. Additionally, another evolutionary algorithm and quality metrics are employed for examination. Comparison results demonstrate that non-dominated solutions obtained by the algorithm have good characteristics. Subsequently, the path corresponding to the knee point of non-dominated solutions is shown. The path is shorter, safer and smoother. This path can be adopted in the later decision-making process. Finally, the above research shows that the revised algorithm can effectively solve the multi-objective path planning problem in static environments.

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Node localization algorithm of wireless sensor networks with mobile beacon node

Cited by 25 publications

References 18 publications

Dynamic Fuzzy-Logic Based Path Planning for Mobility-Assisted Localization in Wireless Sensor Networks

Dynamic Fuzzy-Logic Based Path Planning for Mobility-Assisted Localization in Wireless Sensor Networks

Three-Dimensional Localization Algorithm of WSN Nodes Based on RSSI-TOA and Single Mobile Anchor Node

Mobile Robot Path Planning with a Non-Dominated Sorting Genetic Algorithm

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