Intelligent Weighted Energy Consumption and Delay Optimization for UAV-Assisted MEC Under Malicious Jamming

YANG Helin; ZHENG Mengting; LIU Shuai; XIAO Liang; XIE Xianzhong; XIONG Zehui

doi:10.11999/JEIT230986

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YANG Helin, ZHENG Mengting, LIU Shuai, XIAO Liang, XIE Xianzhong, XIONG Zehui. Intelligent Weighted Energy Consumption and Delay Optimization for UAV-Assisted MEC Under Malicious Jamming[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT230986

Citation:

YANG Helin, ZHENG Mengting, LIU Shuai, XIAO Liang, XIE Xianzhong, XIONG Zehui. Intelligent Weighted Energy Consumption and Delay Optimization for UAV-Assisted MEC Under Malicious Jamming[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT230986

Citation:

YANG Helin, ZHENG Mengting, LIU Shuai, XIAO Liang, XIE Xianzhong, XIONG Zehui. Intelligent Weighted Energy Consumption and Delay Optimization for UAV-Assisted MEC Under Malicious Jamming[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT230986

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Intelligent Weighted Energy Consumption and Delay Optimization for UAV-Assisted MEC Under Malicious Jamming

doi: 10.11999/JEIT230986

1.
School of Informatics, Xiamen University, Xiamen 361005, China
2.
Chongqing Key Laboratory of Computer Network and Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
3.
Pillar of Information Systems Technology and Design, Singapore University of Technology and Design, Singapore 487372

Funds: The National Natural Science Foundation of China (62371408, 62301467, U21A20444, 61971366), The Fundamental Research Funds for the Central Universities (20720220080), Natural Science Foundation of Xiamen(3502Z202371010), Xiaomi Young Talents Program, National Key Research and Development Program of China (2023YFB3107603)

Received Date: 2023-09-08
Rev Recd Date: 2024-04-08

Available Online: 2024-05-07

Abstract

Abstract

In recent years, mounting Mobile Edge Computing (MEC) servers on Unmanned Aerial Vehicle (UAV) to provide services for mobile ground users has been widely researched in academia and industry. However, in malicious jamming environments, how to effectively schedule resources to reduce system delay and energy consumption becomes a key challenge. Therefore, this paper considers a UAV-assisted MEC system under a malicious jammer, where an optimization model is established to minimize the weighted energy consumption and delay by jointly optimizing UAV flight trajectories, resource scheduling, and task allocation. As the optimization problem is difficult to be solved and the malicious jamming behavior is dynamic, a Twin Delayed Deep Deterministic (TD3) policy gradient algorithm is proposed to search for the optimal policy. At the same time, the Prioritized Experience Replay (PER) technique is added to improve the convergence speed and stability of the algorithm, which is highly effective against malicious interference attacks. The simulation results show that the proposed algorithm can effectively reduce the delay and energy consumption, and achieve good convergence and stability compared with other algorithms.
- Unmanned Aerial Vehicle (UAV) communication,
- Mobile Edge Computing (MEC),
- Resource scheduling,
- Anti-jamming,
- Deep Reinforcement Learning (DRL)

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References(19)

References

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