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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2024.8
- 수록면
- 894 - 899 (6page)
- DOI
- 10.9717/kmms.2024.27.8.894
이용수
초록· 키워드
오류제보하기
Task offloading in mobile edge computing(MEC) environments is an important research topic for enhancing user experience. This study proposes a novel approach to optimize task offloading in MEC based on deep reinforcement learning(DRL). This study replaces the LSTM(Long Short-Term Memory) in the existing QOCO(QoE-Oriented Computation Offloading) algorithm with BiLSTM(Bidirectional LSTM). The proposed method uses BiLSTM to improve the capture of dynamic workloads in edge nodes. This results in a performance enhancement of approximately 8% reduction in drop rate and a 6% reduction in the number of dropped tasks, as confirmed through experiments. These results show the advantages of combining DRL and BiLSTM in optimizing task offloading in MEC environments.
목차
ABSTRACT
1. 서론
2. 모바일 엣지 컴퓨팅의 오프로딩
3. 학습 모델 이론
4. BiLSTM 기반 Task Offloading
5. 실험 결과
6. 결론
REFERENCE
참고문헌 (11)
참고문헌 신청
I. Rahmati, H. Shah-Mansouri, and A. Movaghar, “QOCO: A QoE-Oriented Computation Offloading Algorithm Based on Deep Reinforcement Learning for Mobile Edge Computing,” arXiv Preprint, arXiv:2311.02525, 2023.
J. Ahn and B. Lee, “IoT Roaming Service for Seamless IoT Service,” Journal of Korea Multimedia Society, Vol. 23, No. 10, pp. 1258-1269, 2020.
T.X. Tran and D. Pompili, “Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks,” IEEE Transactions on Vehicular Technology, Vol. 68, No. 1, pp. 856-868, 2018.
R. Liang, B. Yang, Z. Yu, X. Cao, D.W.K. Ng, and C. Yuen, “A Multi-Head Ensemble Multi-Task Learning Approach for Dynamical Computation Offloading,” Proceedings of the 2023 IEEE Global Communications Conference, pp. 6079-6084, 2023.
X. Wang, Y. Han, V.C. Leung, D. Niyato, X. Yan, and X. Chen, “Convergence of Edge Computing and Deep Learning: A Comprehensive Survey,” IEEE Communications Surveys and Tutorials, Vol. 22, No. 2, pp. 869-904, 2020.
J. Ahn and B. Lee, “IoT Roaming Service for Seamless IoT Service,” Journal of Korea Multimedia Society, Vol. 23, No. 10, pp. 1258-1269, 2020.
T.X. Tran and D. Pompili, “Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks,” IEEE Transactions on Vehicular Technology, Vol. 68, No. 1, pp. 856-868, 2018.
R. Liang, B. Yang, Z. Yu, X. Cao, D.W.K. Ng, and C. Yuen, “A Multi-Head Ensemble Multi-Task Learning Approach for Dynamical Computation Offloading,” Proceedings of the 2023 IEEE Global Communications Conference, pp. 6079-6084, 2023.
X. Wang, Y. Han, V.C. Leung, D. Niyato, X. Yan, and X. Chen, “Convergence of Edge Computing and Deep Learning: A Comprehensive Survey,” IEEE Communications Surveys and Tutorials, Vol. 22, No. 2, pp. 869-904, 2020.
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