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A power adjusting anchors with improved localization algorithm for mobile wireless sensor networks
In Mobile Wireless Sensor Networks (MWSNs), localization is one of the key technologies since it plays a critical role for many location-aware protocols and applications. Existing range-free localization algorithms for MWSNs are usually based on the Sequential Monte Carlo localization algorithm. The...
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Published in: | International journal of computer mathematics. Computer systems theory 2016-10, Vol.1 (3-4), p.129-140 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | In Mobile Wireless Sensor Networks (MWSNs), localization is one of the key technologies since it plays a critical role for many location-aware protocols and applications. Existing range-free localization algorithms for MWSNs are usually based on the Sequential Monte Carlo localization algorithm. They suffer from low sampling efficiency, high communication computation cost or require high beacon density to achieve high localization accuracy. In this paper, we propose a novel algorithm called 'Power Adjusting Anchors' that outperforms in terms of accuracy. In this algorithm, mobile sensor node localizes its position based on the received power levels transmitted by the neighbouring anchors and by constructing a refined prediction area with the hop-distance estimations between elected anchor nodes. This area will be divided into square grids, and sensor node selects all the grids which owns the highest elections, and then, computes the centroid of such grids. The calculated centroid is considered as the estimated location of the sensor node. In addition, the algorithm addresses the information state provided by the radio communication between sensor nodes and anchor nodes to the success of the localization. Simulation results show that the algorithm is very competitive by achieving high localization accuracy with better localization success. |
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ISSN: | 2379-9927 2379-9935 |
DOI: | 10.1080/23799927.2017.1284902 |