An Improved DV-Hop Localization Algorithm in Wireless Sensor Network

Fu, Caixin; Qian, Zhihong; Ji, Guijuan; Zhao, Yanhang; Wang, Xue

doi:10.1109/ita.2013.9

Cited by 8 publications

(3 citation statements)

References 5 publications

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“…Now, the unknowing node coordinates are computed through the proposed algorithmnamed hyperbolic and mid-perpendicular with centroid (HAMPC)-by incorporating an error correction factor [34] instead of the trilateration technique used in other DV-Hop localization methods. Similar to other DV-Hop methods, the proposed approach also has the three basic steps-i.e., a hop count calculation, followed by an average hop size determination, and then at last a distance estimation technique.…”

Section: Proposed Localization Technique Using Improved Dv-hop Based On Error Correctionmentioning

confidence: 99%

“…With the use of a correction for the distance and average network hop distance, it yields the best results. The letter by C. Fu et al [34] improved the conventional DV-Hop and proposed the Fu DV-Hop, which changes the second and third steps of the conventional DV-Hop. This approach improves the result by correcting the distance, finding the weight for anchor nodes, and, in the third step, validating the coordinates.…”

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confidence: 99%

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SDSWSN—A Secure Approach for a Hop-Based Localization Algorithm Using a Digital Signature in the Wireless Sensor Network

Prashar

Rashid²,

Siddiqui

et al. 2021

Electronics

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Localization and security are among the most dominant tasks of wireless sensor networks (WSN). For applications containing sensitive information on the location parameters of the event, secure localization is mandatory and must not be compromised at any cost. The main task, as if any node is malicious, is to authenticate nodes that are involved in the localization process. In this paper, we propose a secure hop-based algorithm that provides a better localization accuracy. In addition, to maintain the security of the localization process, the digital signature approach is used. Moreover, the impact of malicious nodes on the proposed scheme has also been observed. The proposed approach is also contrasted with the basic DV-Hop and improved DV-Hop based on error correction. From the simulation outcomes, we infer that this secure digital-signature-based localization strategy is quite robust against any node compromise attacks, thereby boosting its precision. Comparisons between the proposed algorithm and the state of the art were made on the grounds of different parameters such as the node quantity, ratio of anchor nodes, and range value towards the localization error.

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Section: Proposed Localization Technique Using Improved Dv-hop Based On Error Correctionmentioning

confidence: 99%

mentioning

confidence: 99%

SDSWSN—A Secure Approach for a Hop-Based Localization Algorithm Using a Digital Signature in the Wireless Sensor Network

Prashar

Rashid²,

Siddiqui

et al. 2021

Electronics

View full text Add to dashboard Cite

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“…The range-based algorithms mainly include TOA localization [1], TDOA localization [2], AOA localization [3], RSSI localization [4] and so on [5][6][7]. The range-free algorithms mainly include Weighted Centroid localization [8], DV-hop localization [9][10][11], RSS-based localization [12] and so on [13]. In the literature [14], there are also some other localization algorithms about mobile anchor node assisted localization in static wireless sensor networks.…”

Section: Introductionmentioning

confidence: 99%

DSLA: Dynamic Sampling Localization Algorithm Based on Virtual Anchor Node

2019

KSII TIIS

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Compared with the localization methods in the static sensor networks, node localization in dynamic sensor networks is more complicated due to the mobility of the nodes. Dynamic Sampling Localization Algorithm Based on Virtual Anchor (DSLA) is proposed in this paper to localize the unknown nodes in dynamic sensor networks. Firstly, DSLA algorithm predicts the speed and movement direction of nodes to determine a sector sampling area. Secondly, a method of calculating the sampling quantity with the size of the sampling area dynamically changing is proposed in this paper. Lastly, the virtual anchor node, i.e., the unknown node that got the preliminary possible area (PLA), assists the other unknown nodes to reduce their PLAs. The last PLA is regarded as a filtering condition to filter out the conflicting sample points quickly. In this way, the filtered sample is close to its real coordinates. The simulation results show that the DSLA algorithm can greatly improve the positioning performance when ensuring the execution time is shorter and the localization coverage rate is higher. The localization error of the DSLA algorithm can be dropped to about 20%.

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