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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 5, 2020.
Abstract: Location is an indispensable segment for Wireless Sensor Network (WSN), since when events happened, we need to know location. The distance vector-hop (DV-Hop) technique is a popular range-free localization algorithm due to its cost efficiency and non-intricate process. Nevertheless, it suffers from poor accuracy, and it is highly influenced by network topology; Especially, more hop counts lead to more errors. In the final phase, least squares are employed to address nonlinear equation, which will gain greater location errors. Aimed at addressing problems mentioned above, an enhanced DV-Hop algorithm based on weighted factor, along with new weighted least squares location technique, is proposed in this paper, and it is called WND-DV-Hop. First, the one hop count of unknown node was corrected by employed received signal strength indication (RSSI) technology. Next, in order to reduce average hop distance error, a weighted coefficient based on beacon node hop count was constructed. A new weighted least squares method was embedded to solve nonlinear equation problem. Finally, considerable experiments were carried out to estimate the performance of WND-DV-Hop, compared the outcomes with state-of-the-art DV-Hop, IDV-Hop, Checkout-DV-Hop, and New-DV-Hop depicted in literature. The empirical findings demonstrated that WND-DV-Hop significantly outperformed other localization algorithms.
Fengrong Han, Izzeldin Ibrahim Mohamed Abdelaziz, Xinni Liu and Kamarul Hawari Ghazali, “An Enhanced Distance Vector-Hop Algorithm using New Weighted Location Method for Wireless Sensor Networks” International Journal of Advanced Computer Science and Applications(IJACSA), 11(5), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110563
@article{Han2020,
title = {An Enhanced Distance Vector-Hop Algorithm using New Weighted Location Method for Wireless Sensor Networks},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110563},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110563},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {5},
author = {Fengrong Han and Izzeldin Ibrahim Mohamed Abdelaziz and Xinni Liu and Kamarul Hawari Ghazali}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.