DOI QR코드

DOI QR Code

Multi-access Edge Computing Scheduler for Low Latency Services

저지연 서비스를 위한 Multi-access Edge Computing 스케줄러

  • Received : 2020.10.05
  • Accepted : 2020.12.04
  • Published : 2020.12.31

Abstract

We have developed a scheduler that additionally consider network performance by extending the Kubernetes developed to manage lots of containers in cloud computing nodes. The network delay adapt characteristics of the compute nodes were learned during server operation and the learned results were utilized to develop placement algorithm by considering the existing measurement units, CPU, memory, and volume together, and it was confirmed that the low delay network service was provided through placement algorithm.

Keywords

References

  1. D. Bernstein, "Containers and Cloud: From LXC to Docker to Kubernetes," in IEEE Cloud Computing, Vol. 1, No. 3, pp. 81-84, 2014. https://doi.org/10.1109/MCC.2014.51
  2. M. Chiang, T. Zhang, "Fog and IoT: An Overview of Research Opportunities," in IEEE Internet of Things Journal, Vol. 3, No. 6, pp. 854-864, 2016. https://doi.org/10.1109/JIOT.2016.2584538
  3. T.H. Kim, et al. "Virtualization and Kubernetes," OSIA Standards & Technology Review, Vol. 33, No. 2, pp. 4-10, 2020 (in Korean).
  4. R. Perez de Prado, S. Garcia-Galan, J.E. Munoz-Exposito, A. Marchewka, N. Ruiz-Reyes, "Smart Containers Schedulers for Microservices Provision in Cloud-Fog-IoT Networks. Challenges and Opportunities," Sensors, Vol. 20, No. 6, pp. 1714, 2020. https://doi.org/10.3390/s20061714
  5. Y.C. Hu, M. Patel, D. Sabella, N. Sprecher, V. Young, "Mobile edge computing-A key technology towards 5G," ETSI white paper, Vol. 11, No. 11, pp. 1-16, 2015.
  6. J. Santos, T. Wauters, B. Volckaert and F. De Turck, "Towards Network-Aware Resource Provisioning in Kubernetes for Fog Computing Applications," 2019 IEEE Conference on Network Softwarization (NetSoft), pp. 351-359, 2019.
  7. T.Y. Kim, J.R. Lee, T.H. Kim, I.G., Chun, J. Park, S. Jin, "Kubernetes Scheduler Framework Implementation with Realtime Resource Monitoring," IEMEK J. Embed. Sys. Appl., Vol. 15, No. 3, pp. 129-137, 2020 (in Korean). https://doi.org/10.14372/IEMEK.2020.15.3.129
  8. D. Santoro, D. Zozin, D. Pizzolli, F. De Pellegrini, S. Cretti, "Foggy: A Platform for Workload Orchestration in a Fog Computing Environment," 2017 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), pp. 231-234, 2017.
  9. S. Sarkar, S. Chatterjee, S. Misra, "Assessment of the Suitability of Fog Computing in the Context of Internet of Things," in IEEE Transactions on Cloud Computing, Vol. 6, No. 1, pp. 46-59, 2018. https://doi.org/10.1109/TCC.2015.2485206
  10. M. Chima Ogbuachi, C. Gore, A. Reale, P. Suskovics, B. Kovacs, "Context-Aware K8S Scheduler for Real Time Distributed 5G Edge Computing Applications," 2019 International Conference on Software, Telecommunications and Computer Networks (SoftCOM), pp. 1-6, 2019.