Edge computing model applied to online Higher Education
DOI:
https://doi.org/10.59169/pentaciencias.v6i7.1310Keywords:
Edge computing; latency; on-line platforms; microservicesAbstract
This study presents the design of an edge computing model focused on improving the student experience in online higher education at the University of Guayaquil, particularly in the School of Mathematical Sciences. The research addresses common technical problems in educational platforms, such as latency and intermittent access, which negatively affect student learning. Through a mixed methodology involving surveys and interviews, the main technical difficulties in the use of online platforms were identified. The results indicate that the implementation of edge computing with microservices can significantly reduce latency and improve the accessibility of educational resources, providing a viable and effective solution. Finally, the installation of edge nodes at strategic points of the university campus is suggested to optimize the technological infrastructure and ensure more reliable and continuous access to online educational resources.
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Alwarafy, A., Al-Thelaya, K. A., Abdallah, M., Schneider, J., & Hamdi, M. (2021). A Survey on Security and Privacy Issues in Edge-Computing-Assisted Internet of Things. IEEE Internet of Things Journal, 8(6), 4004–4022. https://doi.org/10.1109/JIOT.2020.3015432
Aristovnik, A., Karampelas, K., Umek, L., & Ravšelj, D. (2023). Impact of the COVID-19 pandemic on online learning in higher education: a bibliometric analysis. Frontiers in Education, 8(August), 1–13. https://doi.org/10.3389/feduc.2023.1225834
Douch, S., Abid, M. R., Zine-Dine, K., Bouzidi, D., & Benhaddou, D. (2022). Edge Computing Technology Enablers: A Systematic Lecture Study. IEEE Access, 10(June), 69264–69302. https://doi.org/10.1109/ACCESS.2022.3183634
Gao, Z., Cheng, Z., Yang, X., Lu, H., Ye, M., & Diao, W. (2018). ECUE: An Edge Computing System for University Education. Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018, 471–476. https://doi.org/10.1109/ITME.2018.00111
Hossain, M. D., Sultana, T., Akhter, S., Hossain, M. I., Thu, N. T., Huynh, L. N. T., Lee, G. W., & Huh, E. N. (2023). The role of microservice approach in edge computing: Opportunities, challenges, and research directions. ICT Express, 9(6), 1162–1182. https://doi.org/10.1016/j.icte.2023.06.006
Oleghe, O. (2021). Container Placement and Migration in Edge Computing: Concept and Scheduling Models. IEEE Access, 9, 68028–68043. https://doi.org/10.1109/ACCESS.2021.3077550
Paul, P. K. ,. (2022). Edge Computing & Educational Systems: Towards Advanced and Intelligent Learning—A Conceptual Overview. International Journal of Information Science and Computing, 9(1). https://doi.org/10.30954/2348-7437.1.2022.2
Ren, J., Wang, H., Hou, T., Zheng, S., & Tang, C. (2020). Collaborative Edge Computing and Caching with Deep Reinforcement Learning Decision Agents. IEEE Access, 8(2), 120604–120612. https://doi.org/10.1109/ACCESS.2020.3007002
Satyanarayanan, M. (2017). The emergence of edge computing. Computer, 50(1), 30–39. https://doi.org/10.1109/MC.2017.9
Yu, W., Liang, F., He, X., Hatcher, W. G., Lu, C., Lin, J., & Yang, X. (2017). A Survey on the Edge Computing for the Internet of Things. IEEE Access, 6, 6900–6919. https://doi.org/10.1109/ACCESS.2017.2778504
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