Hybrid Strategy of Multiple Optimization Algorithms Applied to 3-D Terrain Node Coverage of Wireless Sensor Network
The key to the problem of node coverage in wireless sensor networks (WSN) is to deploy a limited number of sensors to achieve maximum coverage. This paper studies the hybrid strategies of multiple evolutionary algorithms, and applies them to the problem of WSN node coverage. We first proposed the hy...
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| Veröffentlicht in: | Wireless communications and mobile computing 2021, Vol.2021 (1) |
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| creator | Zhang, Li-Gang Fan, Fang Chu, Shu-Chuan Garg, Akhil Pan, Jeng-Shyang |
| description | The key to the problem of node coverage in wireless sensor networks (WSN) is to deploy a limited number of sensors to achieve maximum coverage. This paper studies the hybrid strategies of multiple evolutionary algorithms, and applies them to the problem of WSN node coverage. We first proposed the hybrid algorithm SFLA-WOA (SWOA) based on Shuffled Frog Leaping Algorithm (SFLA) and Whale Optimization Algorithm (WOA). The SWOA algorithm combines the advantages of SFLA and WOA; that is, it retains the unique evolution model of WOA and also has the excellent co-evolution capability of SFLA. Secondly, using the mutation, crossover and selection operations of the differential evolution (DE) algorithm to further optimize this hybrid algorithm, the SWOA-based SFLA-WOA-DE (SWOAD) algorithm is proposed. In addition, the performance of SWOA and SWOAD has been tested by 30 benchmark functions in the CEC 2017 test set. Experimental results show that the optimization effects of these two algorithms are very outstanding. Finally, the simulation results show that the optimization algorithm proposed in this paper has a good effect on improving the signal coverage of WSN under the actual three-dimensional terrain. |
| doi_str_mv | 10.1155/2021/6690824 |
| format | Article |
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This paper studies the hybrid strategies of multiple evolutionary algorithms, and applies them to the problem of WSN node coverage. We first proposed the hybrid algorithm SFLA-WOA (SWOA) based on Shuffled Frog Leaping Algorithm (SFLA) and Whale Optimization Algorithm (WOA). The SWOA algorithm combines the advantages of SFLA and WOA; that is, it retains the unique evolution model of WOA and also has the excellent co-evolution capability of SFLA. Secondly, using the mutation, crossover and selection operations of the differential evolution (DE) algorithm to further optimize this hybrid algorithm, the SWOA-based SFLA-WOA-DE (SWOAD) algorithm is proposed. In addition, the performance of SWOA and SWOAD has been tested by 30 benchmark functions in the CEC 2017 test set. Experimental results show that the optimization effects of these two algorithms are very outstanding. Finally, the simulation results show that the optimization algorithm proposed in this paper has a good effect on improving the signal coverage of WSN under the actual three-dimensional terrain.</description><identifier>ISSN: 1530-8669</identifier><identifier>EISSN: 1530-8677</identifier><identifier>DOI: 10.1155/2021/6690824</identifier><language>eng</language><publisher>Oxford: Hindawi</publisher><subject>Communication ; Evolutionary algorithms ; Evolutionary computation ; Genetic algorithms ; Heuristic ; Information industry ; Internet of Things ; Mutation ; Nodes ; Optimization ; Optimization algorithms ; Population ; Sensors ; Terrain ; Wireless networks ; Wireless sensor networks</subject><ispartof>Wireless communications and mobile computing, 2021, Vol.2021 (1)</ispartof><rights>Copyright © 2021 Li-Gang Zhang et al.</rights><rights>Copyright © 2021 Li-Gang Zhang et al. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). 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| subjects | Communication Evolutionary algorithms Evolutionary computation Genetic algorithms Heuristic Information industry Internet of Things Mutation Nodes Optimization Optimization algorithms Population Sensors Terrain Wireless networks Wireless sensor networks |
| title | Hybrid Strategy of Multiple Optimization Algorithms Applied to 3-D Terrain Node Coverage of Wireless Sensor Network |
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