과제정보
이 논문은 2023년도 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임 (No. 2021R1A2C2014333).
참고문헌
- Noohani M. Z., Magsi K. U., "A Review of 5G Technology: Architecture, Security and Wide Applications", International Research Journal of Engineering and Technology(IRJET), vol. 7, no. 5, pp. 3440-3471, May 2020.
- Hakak S., Gadekallu T. R., Maddikunta P. K. R., Ramu S. P., Parimala M., De Alwis C., Liyanage M., "Autonomous Vehicles in 5G and beyond: A Survey", Vehicular Communications, vol. 39, Feb. 2022.
- Alenoghena C. O., Ohize H. O., Adejo A. O., Onumanyi A. J., Ohihoin E. E., Balarabe A. I., Okoh S. A., Kolo E., Alenoghena B., "Telemedicine: A Survey of Telecommunication Technologies, Devel- opments, and Challenges", Journal of Sensor and Actuator Networks, vol. 12, no. 2, Mar. 2023.
- Khujamatov K., Khasanov D., Reypnazarov E., Akhmedov N., "Existing Technologies and Solutions in 5G-Enabled IoT for Industrial Automation", Blockchain for 5G-Enabled IoT, pp. 181-221, Apr. 2021.
- Li S., Da Xu L., Zhao S., "5G Internet of Things: A survey", Journal of Industrial Information Integration, vol. 10, Jun. 2018.
- Shayea I., Ergen M., Azmi M. H., Colak S. A., Nordin R., Daradkeh Y. I., "Key Challenges, Drivers and Solutions for Mobility Management in 5G Networks: A Survey", IEEE Access, vol. 8, pp. 172534-172552, Sep. 2020. https://doi.org/10.1109/ACCESS.2020.3023802
- Ojijo M. O., Falowo O. E., "A Survey on Slice Admission Control Strategies and Optimization Schemes in 5G Network", IEEE Access, vol. 8, pp. 14977-14990, Jan. 2020. https://doi.org/10.1109/ACCESS.2020.2967626
- Xu Y., Gui G., Gacanin H., Adachi F., "A Survey on Resource Allocation for 5G Heterogeneous Networks: Current Research, Future Trends, and Challenges", IEEE Communications Surveys & Tutorials, vol. 23, no. 2, pp. 668-695, Feb. 2021. https://doi.org/10.1109/COMST.2021.3059896
- Salhab N., Langar R., Rahim R., "5G Network Slices Resource Orchestration Using Machine Learning Techniques", Computer Networks, vol. 188, Apr. 2021.
- Yan M., Feng G., Zhou J., Sun Y., Liang Y. C., "Intelligent Resource Scheduling for 5G Radio Access Network Slicing", IEEE Transactions on Vehicular Technology, vol. 68, no. 8, pp. 7691-7703, Jun. 2019. https://doi.org/10.1109/TVT.2019.2922668
- Zhang C., Xie Y., Bai H., Yu B., Li W., Gao Y., "A Survey on Federated Learning", Knowledge-Based Systems, vol. 216, Mar. 2021.
- Li Q., Wen Z., Wu Z., Hu S., Wang N., Li Y., Liu X., He B., "A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection", IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 4, pp. 3347-3366, Apr. 2023. https://doi.org/10.1109/TKDE.2021.3124599
- Breiman L., "Random Forests", Machine learning, vol. 45, pp. 5-32, 2001. https://doi.org/10.1023/A:1010933404324
- Hochreiter S., Schmidhuber J., "Long Short-Term Memory", Neural Computation, vol. 9, no. 8, pp. 1735-1780, Nov. 1997. https://doi.org/10.1162/neco.1997.9.8.1735
- Lillicrap T. P., Hunt J. J., Pritzel A., Heess N., Erez T., Tassa Y., Silver D., Wierstra D., "Continuous Control with Deep Reinforcement Learning", arXiv, Sep. 2015.
- Hamilton W., Ying Z., Leskovec J., "Inductive Representation Learning on Large Graphs", Advances in Neural Information Processing Systems, 2017.
- Thantharate A., Paropkari R., Walunj V., Beard C., "DeepSlice: A Deep Learning Approach Towards an Efficient and Reliable Network Slicing in 5G Networks", Annual Ubiquitous Computing, Electronics & Mobile Communication Conference(UEMCON), pp. 762-767, Feb. 2020.
- Song F., Li J., Ma C., Zhang Y., Shi L., Jayakody D. N. K., "Dynamic Virtual Resource Allocation for 5G and Beyond Network Slicing", IEEE Open Journal of Vehicular Technology, vol. 1, pp. 215- 226, Apr. 2020. https://doi.org/10.1109/OJVT.2020.2990072
- Esteves J. J. A., Boubendir A., Guillemin F., Sens P., "A Heuristically assisted Deep Reinforcement Learning Approach for Network Slice Placement", IEEE Transactions on Network and Service Management, vol. 19, no. 4, pp. 4794-4806, Dec. 2022. https://doi.org/10.1109/TNSM.2021.3132103
- Zahedi S. R., Jamali S., Bayat P., "A Power-Efficient and Performance-aware Online Virtual Network Function Placement in SDN/NFV-enabled Networks", Computer Networks, vol. 205, Mar. 2022.
- Zhao S., "Energy Efficient Resource Allocation Method for 5G Access Network Based on Reinforcement Learning Algorithm", Sustainable Energy Technologies and Assessments, vol. 56, Mar. 2023.
- Brik B., Ksentini A., "On Predicting Service-Oriented Network Slices Performances in 5G: A Federated Learning Approach", Local Computer Networks(LCN), pp. 164-171, Nov. 2020.
- Verma R., Sivalingam K. M., "Federated Learning Approach for Auto-Scaling of Virtual Network Function Resource Allocation in 5G-and-Beyond Networks", Cloud Networking(CloudNet), pp. 242-246, Nov. 2022.
- Hamilton W., Ying Z., Leskovec J., "Inductive Representation Learning on Large Graphs", Advances in Neural Information Processing Systems, 2017.