GbLN-PSO Algorithm for indoor localization in wireless sensor network
Localization is one of the issue in Wireless Sensor Network (WSN). The problem is the estimation error in the localization of the node. In this paper, we propose an indoor localization in WSN based on Global best Local Neighbourhood Particle Swarm Optimization (GbLN-PSO) algorithm. Three anchors are...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2020
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/31629/1/Shahkhir_Mozamir_2020_IOP_Conf._Ser.%20_Mater._Sci._Eng._769_012033.pdf |
| Summary: | Localization is one of the issue in Wireless Sensor Network (WSN). The problem is the estimation error in the localization of the node. In this paper, we propose an indoor localization in WSN based on Global best Local Neighbourhood Particle Swarm Optimization (GbLN-PSO) algorithm. Three anchors are used as the distance measurement for each unknown node to be localized. A comparison of the performances of PSO and GbLN-PSO in terms of localization error (accuracy) and computation time is presenting using simulation in Matlab. The result shows that GbLN-PSO improved the accuracy approximately by 0.01% and reduced the computational time by 86.02% compared to PSO technique. |
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