Joint Optimization of Task Offloading and Resource Allocation for Unmanned Aerial Vehicle-assisted Edge Computing Network

ZHOU Xiaotian; YANG Xiaohui; ZHANG Haixia; DENG Yiqin

doi:10.11999/JEIT240411

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ZHOU Xiaotian, YANG Xiaohui, ZHANG Haixia, DENG Yiqin. Joint Optimization of Task Offloading and Resource Allocation for Unmanned Aerial Vehicle-assisted Edge Computing Network[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240411

Citation:

ZHOU Xiaotian, YANG Xiaohui, ZHANG Haixia, DENG Yiqin. Joint Optimization of Task Offloading and Resource Allocation for Unmanned Aerial Vehicle-assisted Edge Computing Network[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240411

Citation:

ZHOU Xiaotian, YANG Xiaohui, ZHANG Haixia, DENG Yiqin. Joint Optimization of Task Offloading and Resource Allocation for Unmanned Aerial Vehicle-assisted Edge Computing Network[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240411

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Joint Optimization of Task Offloading and Resource Allocation for Unmanned Aerial Vehicle-assisted Edge Computing Network

doi: 10.11999/JEIT240411

1.
School of Control Science and Engineering, Shandong University, Jinan 250061, China
2.
Shandong Key Laboratory of Intelligent Communications and Sensing-Computation Integration, Shandong University, Jinan 250061, China

Funds: The Joint Funds of the National Natural Science Foundation of China (U22A2003), The Major Fundamental Research Project of Shandong Provincial Natural Science Foundation (ZR2022ZD02)

Received Date: 2024-05-25
Rev Recd Date: 2024-11-08

Available Online: 2024-11-13

Abstract

Abstract

It can effectively overcome the limitations of the ground environment, expand the network coverage and provide users with convenient computing services, through constructing the air-ground integrated edge computing network with Unmanned Aerial Vehicle (UAV) as the relay. In this paper, with the objective of maximizing the task completion amount, the joint optimization problem of UAV deployment, user-server association and bandwidth allocation is investigated in the context of the UAV assisted multi-user and multi-server edge computing network. The formulated joint optimization problem contains both continuous and discrete variables, which makes itself hard to solve. To this end, a Block Coordinated Descent (BCD) based iterative algorithm is proposed in this paper, involving the optimization tools such as differential evolution and particle swarm optimization. The original problem is decomposed into three sub-problems with the proposed algorithm, which can be solved independently. The optimal solution of the original problem can be approached through the iteration among these three subproblems. Simulation results show that the proposed algorithm can greatly increase the amount of completed tasks, which outperforms the other benchmark algorithms.
- Unmanned Aerial Vehicle (UAV) communication,
- Multi-access edge computing,
- Task offloading,
- Resource allocation

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References(17)

References

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