A hybrid range-free algorithm using dynamic communication range for wireless sensor networks

Location plays a backbone role in networks, since it will great influence basic wireless sensor networks (WSNs) architecture. Distance-Vector Hop (DV-Hop) is a representative range-free localization algorithm, which is widely utilized to locate node position in location-based application. However, w...

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Bibliographic Details
Main Authors: Fengrong, Han, Izzeldin Ibrahim, Mohamed Abdelaziz, Xinni, Liu, Kamarul Hawari, Ghazali, Hao, Wang
Format: Article
Language:English
Published: iJOE 2020
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Online Access:http://umpir.ump.edu.my/id/eprint/28927/1/A%20Hybrid%20Range-free%20Algorithm%20Using%20Dynamic%20Communication.pdf
http://umpir.ump.edu.my/id/eprint/28927/
https://doi.org/10.3991/ijoe.v16i08.14379
https://doi.org/10.3991/ijoe.v16i08.14379
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Summary:Location plays a backbone role in networks, since it will great influence basic wireless sensor networks (WSNs) architecture. Distance-Vector Hop (DV-Hop) is a representative range-free localization algorithm, which is widely utilized to locate node position in location-based application. However, with poor localization accuracy, it cannot satisfy precise location-based application requirement. Consequently, we proposed a hybrid range-free algorithm depends on dynamic communication range to address low localization accuracy problem, named as DCDV-Hop. Firstly, we applied statistical methods to analyze the relationship between location error and hop count under different communication ranges. Thereafter, we employed centroid algorithm to calculate target node coordinate based on hop threshold. Finally, a weighted least square is applied to locate remaining target nodes. We conducted considerable experiments, the results demonstrated that our proposed algorithm DCDV-Hop can effectively reduce accumulate localization error and improve localization accuracy of target nodes, with stable performance. Moreover, maximum localization accuracy reached up to 91.35% and localization error reduced more than 50%, compared with DV-Hop algorithm.