An approach of battery adaptation in wireless sensor network with resource aware in extreme environmental area
A wireless sensor network (WSN) is a distributed wireless system that employs sensor nodes to perform various tasks, including sensing, monitoring, data transmission, and delivering information to users via internet communication. Resource availability in WSNs is a critical factor influencing data d...
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| Published in: | International Journal of Power Electronics and Drive Systems (IJPEDS) Vol. 16; no. 3; p. 1812 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
01.09.2025
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| ISSN: | 2088-8694, 2722-256X |
| Online Access: | Get full text |
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| Summary: | A wireless sensor network (WSN) is a distributed wireless system that employs sensor nodes to perform various tasks, including sensing, monitoring, data transmission, and delivering information to users via internet communication. Resource availability in WSNs is a critical factor influencing data delivery performance. One of the main challenges is the rapid depletion of resources, particularly batteries, which play a pivotal role in the system’s operational sustainability. This study evaluates the impact of battery adaptation through four testing scenarios. The results show that implementing battery adaptation significantly extends system lifespan compared to scenarios without adaptation. In the scenario without both a classification algorithm and adaptation, the system lasts approximately 270 minutes. When battery adaptation is applied without a classification algorithm, the lifespan increases to 330 minutes and 30 seconds. In contrast, the scenario using a classification algorithm without adaptation yields a lifespan of about 185 minutes, while combining the classification algorithm with adaptation extends it to approximately 252 minutes. The findings demonstrate that battery adaptation enhances the longevity and resource efficiency of WSN systems. However, the use of a classification algorithm tends to reduce operational time compared to scenarios that do not employ such algorithms. |
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| ISSN: | 2088-8694 2722-256X |
| DOI: | 10.11591/ijpeds.v16.i3.pp1812-1821 |