A New DV-Hop Location of Wireless Sensor Networks Based on Firefly Algorithm

Lu, JianYin; Zhao, DaQiong

doi:10.1007/978-3-319-98776-7_116

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…In order to obtain more rigorous experimental conclusions, several experiments were conducted in different environments including an anchor node numbers experiment, a communication radius experiment, a sensor numbers experiment, and a scenario sizes experiment. The results were compared with the DV-Hop algorithm, PSODV-Hop algorithm [35], ABCDV-Hop algorithm [36], FADV-Hop algorithm [37], and ISSADV-Hop algorithm [38]. In order to show the experimental results more intuitively and reduce the experimental chance, the normalized average localization error is introduced as the evaluation index of the algorithm, and each experiment is repeated 30 times and the average value is taken.…”

Section: Scenario Settingsmentioning

confidence: 99%

A Hybrid Localization Algorithm for an Adaptive Strategy-Based Distance Vector-Hop and Improved Sparrow Search for Wireless Sensor Networks

Sun,

Wu,

Liu

et al. 2023

Sensors

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Wireless sensor networks (WSNs) are applied in many fields, among which node localization is one of the most important parts. The Distance Vector-Hop (DV-Hop) algorithm is the most widely used range-free localization algorithm, but its localization accuracy is not high enough. In this paper, to solve this problem, a hybrid localization algorithm for an adaptive strategy-based distance vector-hop and improved sparrow search is proposed (HADSS). First, an adaptive hop count strategy is designed to refine the hop count between all sensor nodes, using a hop count correction factor for secondary correction. Compared with the simple method of using multiple communication radii, this mechanism can refine the hop counts between nodes and reduce the error, as well as the communication overhead. Second, the average hop distance of the anchor nodes is calculated using the mean square error criterion. Then, the average hop distance obtained from the unknown nodes is corrected according to a combination of the anchor node trust degree and the weighting method. Compared with the single weighting method, both the global information about the network and the local information about each anchor node are taken into account, which reduces the average hop distance errors. Simulation experiments are conducted to verify the localization performance of the proposed HADSS algorithm by considering the normalized localization error. The simulation results show that the accuracy of the proposed HADSS algorithm is much higher than that of five existing methods.

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Section: Scenario Settingsmentioning

confidence: 99%

A Hybrid Localization Algorithm for an Adaptive Strategy-Based Distance Vector-Hop and Improved Sparrow Search for Wireless Sensor Networks

Sun,

Wu,

Liu

et al. 2023

Sensors

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“…For the application of natural water pipeline leakage, it is necessary to know the leakage location accurately to make targeted remedial measures [ 7 ]. In some special cases, when it is inconvenient, or the staff are unable to enter the monitoring area to carry out survey work, the unique advantages and characteristics of WSN can be used to quickly monitor the surrounding environmental heat, red ultraviolet, sonar, vital signs and seismic wave signals [ 8 ]. The detected physical information, including temperature, light, air humidity, pressure, soil composition, speed, size and movement direction of moving objects, is given to users for observation and processing.…”

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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A New DV-Hop Location of Wireless Sensor Networks Based on Firefly Algorithm

Cited by 2 publications

References 6 publications

A Hybrid Localization Algorithm for an Adaptive Strategy-Based Distance Vector-Hop and Improved Sparrow Search for Wireless Sensor Networks

A Hybrid Localization Algorithm for an Adaptive Strategy-Based Distance Vector-Hop and Improved Sparrow Search for Wireless Sensor Networks

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

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