Node Placement Optimization of Wireless Sensor Networks Using Multi-Objective Adaptive Degressive Ary Number Encoded Genetic Algorithm
The wireless sensor network (WSN) has the advantages of low cost, high monitoring accuracy, good fault tolerance, remote monitoring and convenient maintenance. It has been widely used in various fields. In the WSN, the placement of node sensors has a great impact on its coverage, energy consumption...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-08-01
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| Series: | Algorithms |
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| Online Access: | https://www.mdpi.com/1999-4893/13/8/189 |
| _version_ | 1797560395146199040 |
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| author | Yijie Zhang Mandan Liu |
| author_facet | Yijie Zhang Mandan Liu |
| author_sort | Yijie Zhang |
| collection | DOAJ |
| description | The wireless sensor network (WSN) has the advantages of low cost, high monitoring accuracy, good fault tolerance, remote monitoring and convenient maintenance. It has been widely used in various fields. In the WSN, the placement of node sensors has a great impact on its coverage, energy consumption and some other factors. In order to improve the convergence speed of a node placement optimization algorithm, the encoding method is improved in this paper. The degressive ary number encoding is further extended to a multi-objective optimization problem. Furthermore, the adaptive changing rule of ary number is proposed by analyzing the experimental results of the <i>N</i>-ary number encoded algorithm. Then a multi-objective optimization algorithm adopting the adaptive degressive ary number encoding method has been used in optimizing the node placement in WSN. The experiments show that the proposed adaptive degressive ary number encoded algorithm can improve both the optimization effect and search efficiency when solving the node placement problem. |
| first_indexed | 2024-03-10T17:59:58Z |
| format | Article |
| id | doaj.art-5ab71a7034714141a4ae60e88ad3881f |
| institution | Directory Open Access Journal |
| issn | 1999-4893 |
| language | English |
| last_indexed | 2024-03-10T17:59:58Z |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj.art-5ab71a7034714141a4ae60e88ad3881f2023-11-20T08:58:36ZengMDPI AGAlgorithms1999-48932020-08-0113818910.3390/a13080189Node Placement Optimization of Wireless Sensor Networks Using Multi-Objective Adaptive Degressive Ary Number Encoded Genetic AlgorithmYijie Zhang0Mandan Liu1Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, No. 130, Meilong Road, Shanghai 200237, ChinaKey Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, No. 130, Meilong Road, Shanghai 200237, ChinaThe wireless sensor network (WSN) has the advantages of low cost, high monitoring accuracy, good fault tolerance, remote monitoring and convenient maintenance. It has been widely used in various fields. In the WSN, the placement of node sensors has a great impact on its coverage, energy consumption and some other factors. In order to improve the convergence speed of a node placement optimization algorithm, the encoding method is improved in this paper. The degressive ary number encoding is further extended to a multi-objective optimization problem. Furthermore, the adaptive changing rule of ary number is proposed by analyzing the experimental results of the <i>N</i>-ary number encoded algorithm. Then a multi-objective optimization algorithm adopting the adaptive degressive ary number encoding method has been used in optimizing the node placement in WSN. The experiments show that the proposed adaptive degressive ary number encoded algorithm can improve both the optimization effect and search efficiency when solving the node placement problem.https://www.mdpi.com/1999-4893/13/8/189wireless sensor networksnode placementa fast non-dominated sorted genetic algorithm (NSGA2)degressive ary numberadaptive |
| spellingShingle | Yijie Zhang Mandan Liu Node Placement Optimization of Wireless Sensor Networks Using Multi-Objective Adaptive Degressive Ary Number Encoded Genetic Algorithm Algorithms wireless sensor networks node placement a fast non-dominated sorted genetic algorithm (NSGA2) degressive ary number adaptive |
| title | Node Placement Optimization of Wireless Sensor Networks Using Multi-Objective Adaptive Degressive Ary Number Encoded Genetic Algorithm |
| title_full | Node Placement Optimization of Wireless Sensor Networks Using Multi-Objective Adaptive Degressive Ary Number Encoded Genetic Algorithm |
| title_fullStr | Node Placement Optimization of Wireless Sensor Networks Using Multi-Objective Adaptive Degressive Ary Number Encoded Genetic Algorithm |
| title_full_unstemmed | Node Placement Optimization of Wireless Sensor Networks Using Multi-Objective Adaptive Degressive Ary Number Encoded Genetic Algorithm |
| title_short | Node Placement Optimization of Wireless Sensor Networks Using Multi-Objective Adaptive Degressive Ary Number Encoded Genetic Algorithm |
| title_sort | node placement optimization of wireless sensor networks using multi objective adaptive degressive ary number encoded genetic algorithm |
| topic | wireless sensor networks node placement a fast non-dominated sorted genetic algorithm (NSGA2) degressive ary number adaptive |
| url | https://www.mdpi.com/1999-4893/13/8/189 |
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