Resource Allocation for Unmanned Aerial Vehicle-assisted Mobile Edge Computing to Minimize Weighted Energy Consumption

LI An; DAI Longbin; YU Lisu; WANG Zhen

doi:10.11999/JEIT210832

Volume 44 Issue 11

Nov. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(11): 3858-3865

LI An, DAI Longbin, YU Lisu, WANG Zhen. Resource Allocation for Unmanned Aerial Vehicle-assisted Mobile Edge Computing to Minimize Weighted Energy Consumption[J]. Journal of Electronics & Information Technology, 2022, 44(11): 3858-3865. doi: 10.11999/JEIT210832

Citation:

LI An, DAI Longbin, YU Lisu, WANG Zhen. Resource Allocation for Unmanned Aerial Vehicle-assisted Mobile Edge Computing to Minimize Weighted Energy Consumption[J]. Journal of Electronics & Information Technology, 2022, 44(11): 3858-3865. doi: 10.11999/JEIT210832

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Resource Allocation for Unmanned Aerial Vehicle-assisted Mobile Edge Computing to Minimize Weighted Energy Consumption

doi: 10.11999/JEIT210832

LI An¹,
DAI Longbin¹,
YU Lisu^{1, 2
,
,},
WANG Zhen^{1, 3}

1.
School of Information Engineering, Nanchang University, Nanchang 330031, China
2.
State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
3.
School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China

Funds: The National Natural Science Foundation of China (61761030, 62161024), The Key Research and Development Project of Jiangxi Province (20202BBE53019), China Postdoctoral Science Foundation (2021TQ0136), The State Key Laboratory of Computer Architecture Project (CARCHB202019)

Received Date: 2021-08-13
Rev Recd Date: 2021-10-29

Available Online: 2021-11-14

Publish Date: 2022-11-14

Abstract

Abstract

For the Unmanned Aerial Vehicle (UAV)-assisted Mobile Edge Computing (MEC) system, it is proposed to balance the energy consumption of UAV and ground equipment by adding a weight factor to the energy consumption of ground equipment, considering that their energy consumption is not in the same order of magnitude. At the same time, to meet the requirements of ground equipment tasks, the weighted energy consumption of UAV and ground equipment are minimized by joint optimization of UAV trajectory and system resource allocation. The formulated problem is highly non-convex, thus an alternating optimization based two-stage resource allocation optimization scheme is proposed to solve it. In the first stage, given the unloading power of the ground equipment, the Successive Convex Approximation (SCA) method is used to solve the UAV trajectory optimization, Central Processing Unit (CPU) frequency resource allocation and unloading time allocation. In the second stage, the unloading power allocation of ground equipment is optimized. Such two-stage alternating and iterative optimization is used to find the sub-optimal solution of the original problem. The effectiveness of the proposed scheme in reducing system energy consumption is verified by simulation results.
- Unmanned Aerial Vehicle (UAV),
- Mobile Edge Computing (MEC),
- Successive Convex Approximation (SCA),
- Resource allocation,
- Alternating optimization

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References(19)

References

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