Joint Resource Allocation Optimization of Wireless Sensor Network Based on Edge Computing
Resource allocation has always been a key technology in wireless sensor networks (WSN), but most of the traditional resource allocation algorithms are based on single interface networks. The emergence and development of multi-interface and multichannel networks solve many bottleneck problems of sing...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/5556651 |
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| _version_ | 1832566480884989952 |
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| author | Jie Liu Li Zhu |
| author_facet | Jie Liu Li Zhu |
| author_sort | Jie Liu |
| collection | DOAJ |
| description | Resource allocation has always been a key technology in wireless sensor networks (WSN), but most of the traditional resource allocation algorithms are based on single interface networks. The emergence and development of multi-interface and multichannel networks solve many bottleneck problems of single interface and single channel networks, it also brings new opportunities to the development of wireless sensor networks, but the multi-interface and multichannel technology not only improves the performance of wireless sensor networks but also brings great challenges to the resource allocation of wireless sensor networks. Edge computing changes the traditional centralized cloud computing processing method into a method that reduces computing storage capacity to the edge of the network and faces users and terminals. Realize the advantages of lower latency, higher bandwidth, and fast response. Therefore, this paper proposes a joint optimization algorithm of resource allocation based on edge computing. We establish a wireless sensor allocation model and then propose our algorithm model combined with the advantages of edge computing. Compared with the traditional allocation algorithm (PCOA, MCMH, and TDMA), it can further improve the resource utilization, reduce the network energy consumption, increase network capacity, and reduce the complexity of the schemes. |
| format | Article |
| id | doaj-art-609b0a0e78534623b91f5efc0abba802 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-609b0a0e78534623b91f5efc0abba8022025-02-03T01:03:58ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/55566515556651Joint Resource Allocation Optimization of Wireless Sensor Network Based on Edge ComputingJie Liu0Li Zhu1Jiujiang Radio and Television University, Department of Teaching, Jiujiang 332000, Jiangxi, ChinaSchool of Computer Engineering, Hubei University of Arts and Science, Xiangyang 441053, Hubei, ChinaResource allocation has always been a key technology in wireless sensor networks (WSN), but most of the traditional resource allocation algorithms are based on single interface networks. The emergence and development of multi-interface and multichannel networks solve many bottleneck problems of single interface and single channel networks, it also brings new opportunities to the development of wireless sensor networks, but the multi-interface and multichannel technology not only improves the performance of wireless sensor networks but also brings great challenges to the resource allocation of wireless sensor networks. Edge computing changes the traditional centralized cloud computing processing method into a method that reduces computing storage capacity to the edge of the network and faces users and terminals. Realize the advantages of lower latency, higher bandwidth, and fast response. Therefore, this paper proposes a joint optimization algorithm of resource allocation based on edge computing. We establish a wireless sensor allocation model and then propose our algorithm model combined with the advantages of edge computing. Compared with the traditional allocation algorithm (PCOA, MCMH, and TDMA), it can further improve the resource utilization, reduce the network energy consumption, increase network capacity, and reduce the complexity of the schemes.http://dx.doi.org/10.1155/2021/5556651 |
| spellingShingle | Jie Liu Li Zhu Joint Resource Allocation Optimization of Wireless Sensor Network Based on Edge Computing Complexity |
| title | Joint Resource Allocation Optimization of Wireless Sensor Network Based on Edge Computing |
| title_full | Joint Resource Allocation Optimization of Wireless Sensor Network Based on Edge Computing |
| title_fullStr | Joint Resource Allocation Optimization of Wireless Sensor Network Based on Edge Computing |
| title_full_unstemmed | Joint Resource Allocation Optimization of Wireless Sensor Network Based on Edge Computing |
| title_short | Joint Resource Allocation Optimization of Wireless Sensor Network Based on Edge Computing |
| title_sort | joint resource allocation optimization of wireless sensor network based on edge computing |
| url | http://dx.doi.org/10.1155/2021/5556651 |
| work_keys_str_mv | AT jieliu jointresourceallocationoptimizationofwirelesssensornetworkbasedonedgecomputing AT lizhu jointresourceallocationoptimizationofwirelesssensornetworkbasedonedgecomputing |