Accurate and fast DV-hop localization algorithm in irregular networks

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Abstract

The DV-hop localization algorithm does not depend on any measurement hardware, which only uses hop-counts to describe the Euclidean distance between nodes, it will not generate any additional burden, and thus this lightweight localization algorithm is economical and effective. Unfortunately, nodes generally have irregular distribution in reality, which tends to make deviations during the conversion between hop-counts and Euclidean distance, and as a result, the final estimated locations of nodes tend to deviate from the right location. Therefore, we analyzed the error during the hop-counts and Euclidean distance conversion, derived that the variance of error is related to hop-counts, and used the weighted least square method to correct the deviation. On this basis, we also limit the estimation location range of normal nodes according to the distances relationship between the estimated distances of normal nodes to anchor nodes and the distances of normal nodes estimated location to anchor nodes. Both the theoretical analysis and experimental results show that the proposed algorithm has not only maintained the economic characteristics of DV-hop localization, but also has the high localization accuracy and it can be adapted to various networks with different deployment of nodes.

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Yan, X., Feng, X., & Sun, Z. (2019). Accurate and fast DV-hop localization algorithm in irregular networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11634 LNCS, pp. 329–340). Springer Verlag. https://doi.org/10.1007/978-3-030-24271-8_30

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