Energy-Efficient Task Offloading Based on Differential Evolution in Edge Computing System With Energy Harvesting
To optimize the energy efficiency of edge computing system with energy harvesting, this paper proposes an energy-efficient task offloading method optimized by differential evolution. First, a wireless edge computing network model is established to analyze the energy harvesting, task offloading and t...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9328437/ |
| _version_ | 1828909877659959296 |
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| author | Yingying Sun Chunhe Song Shimao Yu Yiyang Liu Hao Pan Peng Zeng |
| author_facet | Yingying Sun Chunhe Song Shimao Yu Yiyang Liu Hao Pan Peng Zeng |
| author_sort | Yingying Sun |
| collection | DOAJ |
| description | To optimize the energy efficiency of edge computing system with energy harvesting, this paper proposes an energy-efficient task offloading method optimized by differential evolution. First, a wireless edge computing network model is established to analyze the energy harvesting, task offloading and task calculation of the system, as well as the total number of calculated bits and total energy consumption of the system. Second, according to the total number of calculated bits and total energy consumption of the system, an objective function is established to optimize the energy efficiency of system, and a differential evolution based optimization method is proposed, with which the optimal energy efficiency of system calculation, offloading time, calculation time and frequency are obtained. Experimental results show that the proposed method can not only achieve better convergence effect, but also can effectively solve the energy shortage problem of the micro-equipment and extend the service life of the equipment. |
| first_indexed | 2024-12-13T18:33:12Z |
| format | Article |
| id | doaj.art-13f84b201a524af5a69e7938b0797f7e |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T18:33:12Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-13f84b201a524af5a69e7938b0797f7e2022-12-21T23:35:25ZengIEEEIEEE Access2169-35362021-01-019163831639110.1109/ACCESS.2021.30529019328437Energy-Efficient Task Offloading Based on Differential Evolution in Edge Computing System With Energy HarvestingYingying Sun0Chunhe Song1https://orcid.org/0000-0001-8392-1777Shimao Yu2Yiyang Liu3https://orcid.org/0000-0002-7839-050XHao Pan4https://orcid.org/0000-0001-5377-6433Peng Zeng5https://orcid.org/0000-0001-7863-3260College of Information Engineering, Shenyang University of Chemical Technology, Shenyang, ChinaState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, ChinaState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, ChinaState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, ChinaCollege of Information Engineering, Shenyang University of Chemical Technology, Shenyang, ChinaState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, ChinaTo optimize the energy efficiency of edge computing system with energy harvesting, this paper proposes an energy-efficient task offloading method optimized by differential evolution. First, a wireless edge computing network model is established to analyze the energy harvesting, task offloading and task calculation of the system, as well as the total number of calculated bits and total energy consumption of the system. Second, according to the total number of calculated bits and total energy consumption of the system, an objective function is established to optimize the energy efficiency of system, and a differential evolution based optimization method is proposed, with which the optimal energy efficiency of system calculation, offloading time, calculation time and frequency are obtained. Experimental results show that the proposed method can not only achieve better convergence effect, but also can effectively solve the energy shortage problem of the micro-equipment and extend the service life of the equipment.https://ieeexplore.ieee.org/document/9328437/Edge computingtask offloadingenergy harvestingdifferential evolutionary algorithm |
| spellingShingle | Yingying Sun Chunhe Song Shimao Yu Yiyang Liu Hao Pan Peng Zeng Energy-Efficient Task Offloading Based on Differential Evolution in Edge Computing System With Energy Harvesting IEEE Access Edge computing task offloading energy harvesting differential evolutionary algorithm |
| title | Energy-Efficient Task Offloading Based on Differential Evolution in Edge Computing System With Energy Harvesting |
| title_full | Energy-Efficient Task Offloading Based on Differential Evolution in Edge Computing System With Energy Harvesting |
| title_fullStr | Energy-Efficient Task Offloading Based on Differential Evolution in Edge Computing System With Energy Harvesting |
| title_full_unstemmed | Energy-Efficient Task Offloading Based on Differential Evolution in Edge Computing System With Energy Harvesting |
| title_short | Energy-Efficient Task Offloading Based on Differential Evolution in Edge Computing System With Energy Harvesting |
| title_sort | energy efficient task offloading based on differential evolution in edge computing system with energy harvesting |
| topic | Edge computing task offloading energy harvesting differential evolutionary algorithm |
| url | https://ieeexplore.ieee.org/document/9328437/ |
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