Energy-Efficient Task Migration and Path Planning in UAV-Enabled Mobile Edge Computing System
With the rapid development of unmanned aerial vehicles (UAVs) technology and the advent of the 5G era, the role of UAV-enabled mobile edge computing (MEC) system has attracted much attention, especially in the event of some emergencies. However, considering the limited battery life and computing cap...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/4269102 |
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| _version_ | 1850160537184239616 |
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| author | Can Gong Li Wei Deliang Gong Tiantian Li Fang Feng |
| author_facet | Can Gong Li Wei Deliang Gong Tiantian Li Fang Feng |
| author_sort | Can Gong |
| collection | DOAJ |
| description | With the rapid development of unmanned aerial vehicles (UAVs) technology and the advent of the 5G era, the role of UAV-enabled mobile edge computing (MEC) system has attracted much attention, especially in the event of some emergencies. However, considering the limited battery life and computing capabilities of UAVs, it is challenging to provide energy-efficient services for mobile devices. To solve this challenge, we propose an energy-efficient dynamic task migration algorithm (EDTM) that minimizes the total energy consumption of the system while ensuring UAVs system load balance. Based on the improved ant colony algorithm and path elimination strategy, the proposed algorithm comprehensively considers task migration distance between UAVs, the load situation of UAVs, and environmental factors (e.g., wind speed and air density) and finally plans a reasonable task migration path. The simulation results show that the performance of the proposed EDTM is superior to the benchmark schemes. |
| format | Article |
| id | doaj-art-b6876a28d3a74f9d827886609648e893 |
| institution | OA Journals |
| issn | 1099-0526 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-b6876a28d3a74f9d827886609648e8932025-08-20T02:23:08ZengWileyComplexity1099-05262022-01-01202210.1155/2022/4269102Energy-Efficient Task Migration and Path Planning in UAV-Enabled Mobile Edge Computing SystemCan Gong0Li Wei1Deliang Gong2Tiantian Li3Fang Feng4School of Innovation and EntrepreneurshipSchool of Computer and Artificial IntelligenceSchool of Computer and Artificial IntelligenceSchool of Computer and Artificial IntelligenceSchool of Computer and Artificial IntelligenceWith the rapid development of unmanned aerial vehicles (UAVs) technology and the advent of the 5G era, the role of UAV-enabled mobile edge computing (MEC) system has attracted much attention, especially in the event of some emergencies. However, considering the limited battery life and computing capabilities of UAVs, it is challenging to provide energy-efficient services for mobile devices. To solve this challenge, we propose an energy-efficient dynamic task migration algorithm (EDTM) that minimizes the total energy consumption of the system while ensuring UAVs system load balance. Based on the improved ant colony algorithm and path elimination strategy, the proposed algorithm comprehensively considers task migration distance between UAVs, the load situation of UAVs, and environmental factors (e.g., wind speed and air density) and finally plans a reasonable task migration path. The simulation results show that the performance of the proposed EDTM is superior to the benchmark schemes.http://dx.doi.org/10.1155/2022/4269102 |
| spellingShingle | Can Gong Li Wei Deliang Gong Tiantian Li Fang Feng Energy-Efficient Task Migration and Path Planning in UAV-Enabled Mobile Edge Computing System Complexity |
| title | Energy-Efficient Task Migration and Path Planning in UAV-Enabled Mobile Edge Computing System |
| title_full | Energy-Efficient Task Migration and Path Planning in UAV-Enabled Mobile Edge Computing System |
| title_fullStr | Energy-Efficient Task Migration and Path Planning in UAV-Enabled Mobile Edge Computing System |
| title_full_unstemmed | Energy-Efficient Task Migration and Path Planning in UAV-Enabled Mobile Edge Computing System |
| title_short | Energy-Efficient Task Migration and Path Planning in UAV-Enabled Mobile Edge Computing System |
| title_sort | energy efficient task migration and path planning in uav enabled mobile edge computing system |
| url | http://dx.doi.org/10.1155/2022/4269102 |
| work_keys_str_mv | AT cangong energyefficienttaskmigrationandpathplanninginuavenabledmobileedgecomputingsystem AT liwei energyefficienttaskmigrationandpathplanninginuavenabledmobileedgecomputingsystem AT delianggong energyefficienttaskmigrationandpathplanninginuavenabledmobileedgecomputingsystem AT tiantianli energyefficienttaskmigrationandpathplanninginuavenabledmobileedgecomputingsystem AT fangfeng energyefficienttaskmigrationandpathplanninginuavenabledmobileedgecomputingsystem |