Energy-Efficient Clustering and Localization Technique Using Genetic Algorithm in Wireless Sensor Networks
Localization is recognized among the topmost vital features in numerous wireless sensor network (WSN) applications. This paper puts forward energy-efficient clustering and localization centered on genetic algorithm (ECGAL), in which the residual energy, distance estimation, and coverage connection a...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/5541449 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832561454149009408 |
|---|---|
| author | Junfeng Chen Samson Hansen Sackey Joseph Henry Anajemba Xuewu Zhang Yurun He |
| author_facet | Junfeng Chen Samson Hansen Sackey Joseph Henry Anajemba Xuewu Zhang Yurun He |
| author_sort | Junfeng Chen |
| collection | DOAJ |
| description | Localization is recognized among the topmost vital features in numerous wireless sensor network (WSN) applications. This paper puts forward energy-efficient clustering and localization centered on genetic algorithm (ECGAL), in which the residual energy, distance estimation, and coverage connection are developed to form the fitness function. This function is certainly fast to run. The proposed ECGAL exhausts a lesser amount of energy and extends wireless network existence. Finally, the simulations are carried out to assess the performance of the proposed algorithm. Experimental results show that the proposed algorithm approximates the unknown node location and provides minimum localization error. |
| format | Article |
| id | doaj-art-ba33db4c6b384d9288712d1ce521c341 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-ba33db4c6b384d9288712d1ce521c3412025-02-03T01:25:02ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/55414495541449Energy-Efficient Clustering and Localization Technique Using Genetic Algorithm in Wireless Sensor NetworksJunfeng Chen0Samson Hansen Sackey1Joseph Henry Anajemba2Xuewu Zhang3Yurun He4College of Internet of Things Engineering, Hohai University, Changzhou 213022, ChinaCollege of Internet of Things Engineering, Hohai University, Changzhou 213022, ChinaCollege of Internet of Things Engineering, Hohai University, Changzhou 213022, ChinaCollege of Internet of Things Engineering, Hohai University, Changzhou 213022, ChinaCollege of Internet of Things Engineering, Hohai University, Changzhou 213022, ChinaLocalization is recognized among the topmost vital features in numerous wireless sensor network (WSN) applications. This paper puts forward energy-efficient clustering and localization centered on genetic algorithm (ECGAL), in which the residual energy, distance estimation, and coverage connection are developed to form the fitness function. This function is certainly fast to run. The proposed ECGAL exhausts a lesser amount of energy and extends wireless network existence. Finally, the simulations are carried out to assess the performance of the proposed algorithm. Experimental results show that the proposed algorithm approximates the unknown node location and provides minimum localization error.http://dx.doi.org/10.1155/2021/5541449 |
| spellingShingle | Junfeng Chen Samson Hansen Sackey Joseph Henry Anajemba Xuewu Zhang Yurun He Energy-Efficient Clustering and Localization Technique Using Genetic Algorithm in Wireless Sensor Networks Complexity |
| title | Energy-Efficient Clustering and Localization Technique Using Genetic Algorithm in Wireless Sensor Networks |
| title_full | Energy-Efficient Clustering and Localization Technique Using Genetic Algorithm in Wireless Sensor Networks |
| title_fullStr | Energy-Efficient Clustering and Localization Technique Using Genetic Algorithm in Wireless Sensor Networks |
| title_full_unstemmed | Energy-Efficient Clustering and Localization Technique Using Genetic Algorithm in Wireless Sensor Networks |
| title_short | Energy-Efficient Clustering and Localization Technique Using Genetic Algorithm in Wireless Sensor Networks |
| title_sort | energy efficient clustering and localization technique using genetic algorithm in wireless sensor networks |
| url | http://dx.doi.org/10.1155/2021/5541449 |
| work_keys_str_mv | AT junfengchen energyefficientclusteringandlocalizationtechniqueusinggeneticalgorithminwirelesssensornetworks AT samsonhansensackey energyefficientclusteringandlocalizationtechniqueusinggeneticalgorithminwirelesssensornetworks AT josephhenryanajemba energyefficientclusteringandlocalizationtechniqueusinggeneticalgorithminwirelesssensornetworks AT xuewuzhang energyefficientclusteringandlocalizationtechniqueusinggeneticalgorithminwirelesssensornetworks AT yurunhe energyefficientclusteringandlocalizationtechniqueusinggeneticalgorithminwirelesssensornetworks |