Energy-efficient task allocation for reliable parallel computation of cluster-based wireless sensor network in edge computing
To efficiently complete a complex computation task, the complex task should be decomposed into sub-computation tasks that run parallel in edge computing. Wireless Sensor Network (WSN) is a typical application of parallel computation. To achieve highly reliable parallel computation for wireless senso...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2023-04-01
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| Series: | Digital Communications and Networks |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352864822001365 |
| _version_ | 1797829560596692992 |
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| author | Jiabao Wen Jiachen Yang Tianying Wang Yang Li Zhihan Lv |
| author_facet | Jiabao Wen Jiachen Yang Tianying Wang Yang Li Zhihan Lv |
| author_sort | Jiabao Wen |
| collection | DOAJ |
| description | To efficiently complete a complex computation task, the complex task should be decomposed into sub-computation tasks that run parallel in edge computing. Wireless Sensor Network (WSN) is a typical application of parallel computation. To achieve highly reliable parallel computation for wireless sensor network, the network's lifetime needs to be extended. Therefore, a proper task allocation strategy is needed to reduce the energy consumption and balance the load of the network. This paper proposes a task model and a cluster-based WSN model in edge computing. In our model, different tasks require different types of resources and different sensors provide different types of resources, so our model is heterogeneous, which makes the model more practical. Then we propose a task allocation algorithm that combines the Genetic Algorithm (GA) and the Ant Colony Optimization (ACO) algorithm. The algorithm concentrates on energy conservation and load balancing so that the lifetime of the network can be extended. The experimental result shows the algorithm's effectiveness and advantages in energy conservation and load balancing. |
| first_indexed | 2024-04-09T13:22:08Z |
| format | Article |
| id | doaj.art-7eac5bcf1256492d9f038c7e44d4455d |
| institution | Directory Open Access Journal |
| issn | 2352-8648 |
| language | English |
| last_indexed | 2024-04-09T13:22:08Z |
| publishDate | 2023-04-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Digital Communications and Networks |
| spelling | doaj.art-7eac5bcf1256492d9f038c7e44d4455d2023-05-11T04:24:18ZengKeAi Communications Co., Ltd.Digital Communications and Networks2352-86482023-04-0192473482Energy-efficient task allocation for reliable parallel computation of cluster-based wireless sensor network in edge computingJiabao Wen0Jiachen Yang1Tianying Wang2Yang Li3Zhihan Lv4School of Electrical and Information Engineering, Tianjin University, Tianjin, 300072, ChinaSchool of Electrical and Information Engineering, Tianjin University, Tianjin, 300072, China; Corresponding author.School of Electrical and Information Engineering, Tianjin University, Tianjin, 300072, ChinaCollege of Mechanical and Electrical Engineering, Shihezi University, Xinjiang, 832003, ChinaSchool of Data Science and Software Engineering, Qingdao University, Qingdao, 266000, ChinaTo efficiently complete a complex computation task, the complex task should be decomposed into sub-computation tasks that run parallel in edge computing. Wireless Sensor Network (WSN) is a typical application of parallel computation. To achieve highly reliable parallel computation for wireless sensor network, the network's lifetime needs to be extended. Therefore, a proper task allocation strategy is needed to reduce the energy consumption and balance the load of the network. This paper proposes a task model and a cluster-based WSN model in edge computing. In our model, different tasks require different types of resources and different sensors provide different types of resources, so our model is heterogeneous, which makes the model more practical. Then we propose a task allocation algorithm that combines the Genetic Algorithm (GA) and the Ant Colony Optimization (ACO) algorithm. The algorithm concentrates on energy conservation and load balancing so that the lifetime of the network can be extended. The experimental result shows the algorithm's effectiveness and advantages in energy conservation and load balancing.http://www.sciencedirect.com/science/article/pii/S2352864822001365Wireless sensor networkParallel computationTask allocationGenetic algorithmAnt colony optimization algorithmEnergy-efficient |
| spellingShingle | Jiabao Wen Jiachen Yang Tianying Wang Yang Li Zhihan Lv Energy-efficient task allocation for reliable parallel computation of cluster-based wireless sensor network in edge computing Digital Communications and Networks Wireless sensor network Parallel computation Task allocation Genetic algorithm Ant colony optimization algorithm Energy-efficient |
| title | Energy-efficient task allocation for reliable parallel computation of cluster-based wireless sensor network in edge computing |
| title_full | Energy-efficient task allocation for reliable parallel computation of cluster-based wireless sensor network in edge computing |
| title_fullStr | Energy-efficient task allocation for reliable parallel computation of cluster-based wireless sensor network in edge computing |
| title_full_unstemmed | Energy-efficient task allocation for reliable parallel computation of cluster-based wireless sensor network in edge computing |
| title_short | Energy-efficient task allocation for reliable parallel computation of cluster-based wireless sensor network in edge computing |
| title_sort | energy efficient task allocation for reliable parallel computation of cluster based wireless sensor network in edge computing |
| topic | Wireless sensor network Parallel computation Task allocation Genetic algorithm Ant colony optimization algorithm Energy-efficient |
| url | http://www.sciencedirect.com/science/article/pii/S2352864822001365 |
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