Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm
Abstract In wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2021-04-01
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| Series: | EURASIP Journal on Wireless Communications and Networking |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13638-021-01951-1 |
| _version_ | 1818652778937974784 |
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| author | Yang Wang Feifan Wang Yujun Zhu Yiyang Liu Chuanxin Zhao |
| author_facet | Yang Wang Feifan Wang Yujun Zhu Yiyang Liu Chuanxin Zhao |
| author_sort | Yang Wang |
| collection | DOAJ |
| description | Abstract In wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an improved cuckoo search (ICS) algorithm is proposed. This algorithm is based on the traditional cuckoo search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility. |
| first_indexed | 2024-12-17T02:27:25Z |
| format | Article |
| id | doaj.art-50ab3157646a41bda553ea00a8f12fc0 |
| institution | Directory Open Access Journal |
| issn | 1687-1499 |
| language | English |
| last_indexed | 2024-12-17T02:27:25Z |
| publishDate | 2021-04-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Wireless Communications and Networking |
| spelling | doaj.art-50ab3157646a41bda553ea00a8f12fc02022-12-21T22:07:04ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14992021-04-012021111810.1186/s13638-021-01951-1Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithmYang Wang0Feifan Wang1Yujun Zhu2Yiyang Liu3Chuanxin Zhao4Internet of Things Technology and Application Laboratory, Anhui Normal UniversityInternet of Things Technology and Application Laboratory, Anhui Normal UniversityInternet of Things Technology and Application Laboratory, School of Computer and Information, Anhui Normal UniversityInternet of Things Technology and Application Laboratory, Anhui Normal UniversityInternet of Things Technology and Application Laboratory, Anhui Normal UniversityAbstract In wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an improved cuckoo search (ICS) algorithm is proposed. This algorithm is based on the traditional cuckoo search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility.https://doi.org/10.1186/s13638-021-01951-1Wireless rechargeable sensor networkNode deploymentDeployment optimizationCuckoo search |
| spellingShingle | Yang Wang Feifan Wang Yujun Zhu Yiyang Liu Chuanxin Zhao Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm EURASIP Journal on Wireless Communications and Networking Wireless rechargeable sensor network Node deployment Deployment optimization Cuckoo search |
| title | Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm |
| title_full | Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm |
| title_fullStr | Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm |
| title_full_unstemmed | Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm |
| title_short | Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm |
| title_sort | optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm |
| topic | Wireless rechargeable sensor network Node deployment Deployment optimization Cuckoo search |
| url | https://doi.org/10.1186/s13638-021-01951-1 |
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