Abstract
Location awareness is very crucial for almost existing sensor network applications. However, using Global Positioning System (GPS) receivers to every node is very expensive. Therefore, anchor based localization techniques are proposed. The lack of anchors in some WSNs lead to the appearance of multi-hop localization, which permits to localize nodes even if they are far from anchors. One of the well-known multi-hop localization algorithms is the Distance Vector- Hop algorithm (DV-Hop). Although its simplicity, DV-Hop presents some deficiencies in terms of localization accuracy. Therefore, to deal with this issue, we propose in this paper an improvement of DV-Hop algorithm, called Regularized Least Square DV-Hop Localization Algorithm for multihop wireless sensors networks. The proposed solution improves the location accuracy of sensor nodes within their sensing field in both isotropic and anisotropic networks. We used the double Least Square localization method and the statistical filtering optimization strategy, which is the Regularized Least Square method. Simulation results prove that the proposed algorithm outperforms the original DV-Hop algorithm with up to 60%, as well as other related works, in terms of localization accuracy.
Highlights
N OWADAYS, the Internet of Things (IoT) is a promising technology which aims to a revolutionary development and connects the global world via smart connected physical devices
This paper evaluates the performance of multi-hop localization algorithms used in range-free cases, such as Distance VectorHop algorithm (DV-Hop), Improved DV-Hop (IDV-Hop) [29], and the Weighted DV-Hop (WDV-Hop) [30]
Other localization algorithms from the literature including the original DV-hop [19], enhanced Weighted Centroid DV-Hop (EWCL) algorithm [36], Improved Recursive (IR-DV-hop) DV-Hop algorithm [37], the localization algorithm based on the improved DV-Hop and differential evolution (DE) algorithms (DEIDV-HOP) [38], a multi-objective DV-Hop localization algorithm based on NSGA-II (NSGA-II-DV-Hop) [39] and multihop range-free localization algorithm based on Least Square Regularized Regression (LSRR) [26]
Summary
N OWADAYS, the Internet of Things (IoT) is a promising technology which aims to a revolutionary development and connects the global world via smart connected physical devices. Authors in [28] proposed a Weighted Hyperbolic DVHop Positioning Node Localization Algorithm in WSNs. This paper evaluates the performance of multi-hop localization algorithms used in range-free cases, such as DV-Hop, Improved DV-Hop (IDV-Hop) [29], and the Weighted DV-Hop (WDV-Hop) [30]. Authors in [32] proposed a range-free localization algorithm for anisotropic WSNs, in which the position of the unknown node is properly estimated regarding a new reliable anchor selection strategy that guarantees a good estimation accuraty of the distance. We propose a multi-hop range-free localization algorithm based on Least Square Regularized Regression for distances estimation in WSNs. The aim of our work is minimizing the localization error. The hop-count between the unknown nodes and anchors are computed and presented as matrix Hcn of dimension na × nn, where nn presented the number of unknown nodes
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