A novel topology optimization of coverage-oriented strategy for wireless sensor networks
Aiming at the key optimization problems of wireless sensor networks in complex industrial application environments, such as the optimum coverage and the reliability of the network, a novel topology optimization of coverage-oriented strategy for wireless sensor networks based on the wolf pack algorit...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-04-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147721992298 |
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| _version_ | 1832547374444052480 |
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| author | Shuxin Wang Hairong You Yinggao Yue Li Cao |
| author_facet | Shuxin Wang Hairong You Yinggao Yue Li Cao |
| author_sort | Shuxin Wang |
| collection | DOAJ |
| description | Aiming at the key optimization problems of wireless sensor networks in complex industrial application environments, such as the optimum coverage and the reliability of the network, a novel topology optimization of coverage-oriented strategy for wireless sensor networks based on the wolf pack algorithm is proposed. Combining the characteristics of topology structure of wireless sensor networks and the optimization idea of the wolf pack algorithm redefines the group’s wandering and surprise behavior. A novel head wolf mutation strategy is proposed, which increases the neighborhood search range of the optimal solution, enhances the uniformity of wolf pack distribution and the ergodicity ability of the wolf pack search, and greatly improves the calculation speed and the accuracy of the wolf pack algorithm. With the same probability, the cluster heads are randomly selected periodically, and the overall energy consumption of wireless sensor networks is evenly distributed to the sensor node to realize the balanced distribution of the data of the member nodes in the cluster and complete the design of the topology optimization of wireless sensor networks. Through algorithm simulation and result analysis, compared with the particle swarm optimization algorithm and artificial fish swarm algorithm, the wolf swarm algorithm shows its advantages in terms of the residual energy of the sensor node, the average transmission delay, the average packet delivery rate, and the coverage of the network. Among them, compared with the particle swarm optimization algorithm and artificial fish swarm algorithm, the remaining energy of nodes has increased by 9.5% and 15.5% and the average coverage of the network has increased by 10.5% and 5.6%, respectively. |
| format | Article |
| id | doaj-art-9086b1464c1c4565a26d354ab471ccf3 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2021-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-9086b1464c1c4565a26d354ab471ccf32025-02-03T06:45:05ZengWileyInternational Journal of Distributed Sensor Networks1550-14772021-04-011710.1177/1550147721992298A novel topology optimization of coverage-oriented strategy for wireless sensor networksShuxin Wang0Hairong You1Yinggao Yue2Li Cao3Oujiang College, Wenzhou University, Wenzhou, P.R. ChinaSchool of Information Science & Engineering, Northeastern University, Shenyang, P.R. ChinaComputer School, Hubei University of Arts and Science, Xiangyang, P.R. ChinaOujiang College, Wenzhou University, Wenzhou, P.R. ChinaAiming at the key optimization problems of wireless sensor networks in complex industrial application environments, such as the optimum coverage and the reliability of the network, a novel topology optimization of coverage-oriented strategy for wireless sensor networks based on the wolf pack algorithm is proposed. Combining the characteristics of topology structure of wireless sensor networks and the optimization idea of the wolf pack algorithm redefines the group’s wandering and surprise behavior. A novel head wolf mutation strategy is proposed, which increases the neighborhood search range of the optimal solution, enhances the uniformity of wolf pack distribution and the ergodicity ability of the wolf pack search, and greatly improves the calculation speed and the accuracy of the wolf pack algorithm. With the same probability, the cluster heads are randomly selected periodically, and the overall energy consumption of wireless sensor networks is evenly distributed to the sensor node to realize the balanced distribution of the data of the member nodes in the cluster and complete the design of the topology optimization of wireless sensor networks. Through algorithm simulation and result analysis, compared with the particle swarm optimization algorithm and artificial fish swarm algorithm, the wolf swarm algorithm shows its advantages in terms of the residual energy of the sensor node, the average transmission delay, the average packet delivery rate, and the coverage of the network. Among them, compared with the particle swarm optimization algorithm and artificial fish swarm algorithm, the remaining energy of nodes has increased by 9.5% and 15.5% and the average coverage of the network has increased by 10.5% and 5.6%, respectively.https://doi.org/10.1177/1550147721992298 |
| spellingShingle | Shuxin Wang Hairong You Yinggao Yue Li Cao A novel topology optimization of coverage-oriented strategy for wireless sensor networks International Journal of Distributed Sensor Networks |
| title | A novel topology optimization of coverage-oriented strategy for wireless sensor networks |
| title_full | A novel topology optimization of coverage-oriented strategy for wireless sensor networks |
| title_fullStr | A novel topology optimization of coverage-oriented strategy for wireless sensor networks |
| title_full_unstemmed | A novel topology optimization of coverage-oriented strategy for wireless sensor networks |
| title_short | A novel topology optimization of coverage-oriented strategy for wireless sensor networks |
| title_sort | novel topology optimization of coverage oriented strategy for wireless sensor networks |
| url | https://doi.org/10.1177/1550147721992298 |
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