지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2024.8
- 수록면
- 1,183 - 1,195 (13page)
- DOI
- 10.7840/kics.2024.49.8.1183
이용수
초록· 키워드
오류제보하기
In recent years, edge computing has acquired a significant interest in developing and deploying applications by bringing computational resources close to the data source, improving the quality of application experience, and optimizing system resource usage. Edge node deployment strategies in existing studies suppose that once edge nodes are registered in an edge computing system, they will permanently operate with high availability. However, deploying the orchestration solutions in edge computing environments is challenging because of the mobility of edge nodes (mobile nodes) and low availability due to energy limitations and network unstable. To solve this problem, we propose a standalone management structure for deploying mobile nodes in an edge-cloud computing environment that enables mobility support in a Kubernetes-based Edge-Cloud infrastructure. We develop self-managed mobile edge nodes constructed as standalone nodes, ensuring workloads continue operating even when the connection between the mobile node and the cloud is interrupted. Additionally, we consider an energy-aware deployment strategy through energy monitoring and workload scaling schemes at the self-managed mobile node. In this paper, we also implement the proposed architecture on the infrastructure built and established by OpenStack and KubeEdge open-source projects. Measurements show the feasibility of the proposed architecture in deploying mobile nodes that operate independently.
목차
ABSTRACT
Ⅰ. Introduction
Ⅱ. Mobile Edge-Cloud Environment
Ⅲ. Proposed Architecture of Self-Managed Mobile Edge Node
Ⅳ. Implementation
Ⅴ. Conclusion and Future Works
References
참고문헌 (23)
참고문헌 신청
G. Carvalho, B. Cabral, V. Pereira, and J. Bernardino, “Edge computing: Current trends, research challenges, and future directions,” Comput., vol. 103, pp. 993-1023, 2021. (https://doi.org/10.1007/s00607-020-00896-5)
Q. Luo, S. Hu, C. Li, G. Li, and W. Shi, “Resource scheduling in edge computing: A survey,” in IEEE Commun. Surv. & Tuts., vol. 23, no. 4, pp. 2131-2165, Fourth quarter 2021. (https://doi.org/10.1109/COMST.2021.3106401)
Y. Mansouri and M. A. Babar, “A review of edge computing: Features and resource virtualization,” J. Parallel and Distrib. Comput., vol. 150, pp. 155-183, 2021. (https://doi.org/10.1016/j.jpdc.2020.12.015)
O. Bentaleb, A. S. Belloum, A. Sebaa, and A. El-Maouhab, “Containerization technologies: Taxonomies, applications and challenges,” J. Supercomputing, vol. 78, no. 1, pp. 1144-1181, 2022. (https://doi.org/10.1007/s11227-021-03914-1)
S. Hu, W. Shi, and G. Li, “CEC: A containerized edge computing framework for dynamic resource provisioning,” in IEEE Trans. Mobile Comput., vol. 22, no. 7, pp. 3840-3854, Jul. 2023. (https://doi.org/10.1109/TMC.2022.3147800)
Q. Luo, S. Hu, C. Li, G. Li, and W. Shi, “Resource scheduling in edge computing: A survey,” in IEEE Commun. Surv. & Tuts., vol. 23, no. 4, pp. 2131-2165, Fourth quarter 2021. (https://doi.org/10.1109/COMST.2021.3106401)
Y. Mansouri and M. A. Babar, “A review of edge computing: Features and resource virtualization,” J. Parallel and Distrib. Comput., vol. 150, pp. 155-183, 2021. (https://doi.org/10.1016/j.jpdc.2020.12.015)
O. Bentaleb, A. S. Belloum, A. Sebaa, and A. El-Maouhab, “Containerization technologies: Taxonomies, applications and challenges,” J. Supercomputing, vol. 78, no. 1, pp. 1144-1181, 2022. (https://doi.org/10.1007/s11227-021-03914-1)
S. Hu, W. Shi, and G. Li, “CEC: A containerized edge computing framework for dynamic resource provisioning,” in IEEE Trans. Mobile Comput., vol. 22, no. 7, pp. 3840-3854, Jul. 2023. (https://doi.org/10.1109/TMC.2022.3147800)
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