Dynamic Provisioning of Container Registries in Edge Computing Infrastructures
Resumo
The emergence of applications with latency-sensitive demands highlighted some limitations of cloud computing and led to the advent of edge computing. Accompanied by challenges such as mobile users and limited resources, this decentralized computing paradigm is frequently associated with container-based virtualization. However, the traditional container registry has significant limitations in properly provisioning container images on edge infrastructures. Consequently, previous authors focused on improving the application provisioning process by modifying this entity. This paper examines previous attempts at decentralizing container registries in edge computing infrastructures. Based on our initial comparison results, we propose a strategy for dynamically provisioning and deprovisioning container registries based on each server’s storage and the infrastructure’s application demands. The final results show that our strategy can optimize resource utilization in the infrastructure, but needs adjustments to reach the lowest overall latency for application users.
Referências
Alibaba (2022). dragonflyoss/dragonfly2: Dragonfly is an intelligent p2p based image and file distribution system, it also provides a variety of enterprise-level (efficiency, stability, safety, low-cost) product features.
Aral, A., De Maio, V., and Brandic, I. (2021). Ares: Reliable and sustainable edge provisioning for wireless sensor networks. IEEE Transactions on Sustainable Computing, 7(4):761–773.
Bai, F. and Helmy, A. (2004). A survey of mobility models. Wireless Adhoc Networks. University of Southern California, USA, 206:147.
Becker, S., Schmidt, F., and Kao, O. (2021). Edgepier: P2p-based container image distribution in edge computing environments. In 2021 IEEE International Performance, Computing, and Communications Conference (IPCCC), pages 1–8. IEEE.
Buyya, R., Srirama, S. N., Casale, G., Calheiros, R., Simmhan, Y., Varghese, B., Gelenbe, E., Javadi, B., Vaquero, L. M., Netto, M. A., et al. (2018). A manifesto for future generation cloud computing: Research directions for the next decade. ACM computing surveys (CSUR), 51(5):1–38.
Cao, K., Liu, Y., Meng, G., and Sun, Q. (2020). An overview on edge computing research. IEEE access, 8:85714–85728.
Dijkstra, E. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1):269–271.
Gazzetti, M., Reale, A., Katrinis, K., and Corradi, A. (2017). Scalable linux container provisioning in fog and edge computing platforms. In European Conference on Parallel Processing, pages 304–315. Springer.
Harter, T., Salmon, B., Liu, R., Arpaci-Dusseau, A. C., and Arpaci-Dusseau, R. H. (2016). Slacker: Fast distribution with lazy docker containers. In 14th USENIX Conference on File and Storage Technologies (FAST 16), pages 181–195.
Ismail, B. I., Goortani, E. M., Ab Karim, M. B., Tat, W. M., Setapa, S., Luke, J. Y., and Hoe, O. H. (2015). Evaluation of docker as edge computing platform. In 2015 IEEE conference on open systems (ICOS), pages 130–135. IEEE.
Ismail, L. and Materwala, H. (2021). Escove: energy-sla-aware edge–cloud computation offloading in vehicular networks. Sensors, 21(15):5233.
Kangjin, W., Yong, Y., Ying, L., Hanmei, L., and Lin, M. (2017). Fid: A faster image distribution system for docker platform. In 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS* W), pages 191–198. IEEE.
Klas, G. (2017). Edge computing and the role of cellular networks. Computer, 50(10):40–49.
Knob, L. A. D., Faticanti, F., Ferreto, T., and Siracusa, D. (2021). Community-based placement of registries to speed up application deployment on edge computing. In 2021 IEEE International Conference on Cloud Engineering (IC2E), pages 147–153. IEEE.
Liang, M., Shen, S., Li, D., Mi, H., and Liu, F. (2016). Hdid: An efficient hybrid docker image distribution system for datacenters. In National Software Application Conference, pages 179–194. Springer.
Luo, Q., Hu, S., Li, C., Li, G., and Shi, W. (2021). Resource scheduling in edge computing: A survey. IEEE Communications Surveys & Tutorials, 23(4):2131–2165.
MacQueen, J. (1967). Classification and analysis of multivariate observations. In Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability, pages 281–297.
Mansouri, Y. and Babar, M. A. (2021). A review of edge computing: Features and resource virtualization. Journal of Parallel and Distributed Computing, 150:155–183.
Mao, Y., You, C., Zhang, J., Huang, K., and Letaief, K. B. (2017). A survey on mobile edge computing: The communication perspective. IEEE communications surveys & tutorials, 19(4):2322–2358.
Merkel, D. et al. (2014). Docker: lightweight linux containers for consistent development and deployment. Linux j, 239(2):2.
Rejiba, Z., Masip-Bruin, X., and Marín-Tordera, E. (2019). A survey on mobility-induced service migration in the fog, edge, and related computing paradigms. ACM Computing Surveys (CSUR), 52(5):1–33.
Satyanarayanan, M. (2017). The emergence of edge computing. Computer, 50(1):30–39.
Satyanarayanan, M., Bahl, P., Caceres, R., and Davies, N. (2009). The case for vm-based cloudlets in mobile computing. IEEE pervasive Computing, 8(4):14–23.
Souza, P., Kayser, C., Roges, L., and Ferreto, T. (2023a). Thea-a qos, privacy, and power-aware algorithm for placing applications on federated edges. In 2023 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pages 136–143. IEEE.
Souza, P. S., Ferreto, T., and Calheiros, R. N. (2023b). Edgesimpy: Python-based modeling and simulation of edge computing resource management policies. Future Generation Computer Systems.
Uber (2022). uber/kraken: P2p docker registry capable of distributing tbs of data in seconds.
Yao, H., Bai, C., Zeng, D., Liang, Q., and Fan, Y. (2015). Migrate or not? exploring virtual machine migration in roadside cloudlet-based vehicular cloud. Concurrency and Computation: Practice and Experience, 27(18):5780–5792.
Aral, A., De Maio, V., and Brandic, I. (2021). Ares: Reliable and sustainable edge provisioning for wireless sensor networks. IEEE Transactions on Sustainable Computing, 7(4):761–773.
Bai, F. and Helmy, A. (2004). A survey of mobility models. Wireless Adhoc Networks. University of Southern California, USA, 206:147.
Becker, S., Schmidt, F., and Kao, O. (2021). Edgepier: P2p-based container image distribution in edge computing environments. In 2021 IEEE International Performance, Computing, and Communications Conference (IPCCC), pages 1–8. IEEE.
Buyya, R., Srirama, S. N., Casale, G., Calheiros, R., Simmhan, Y., Varghese, B., Gelenbe, E., Javadi, B., Vaquero, L. M., Netto, M. A., et al. (2018). A manifesto for future generation cloud computing: Research directions for the next decade. ACM computing surveys (CSUR), 51(5):1–38.
Cao, K., Liu, Y., Meng, G., and Sun, Q. (2020). An overview on edge computing research. IEEE access, 8:85714–85728.
Dijkstra, E. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1):269–271.
Gazzetti, M., Reale, A., Katrinis, K., and Corradi, A. (2017). Scalable linux container provisioning in fog and edge computing platforms. In European Conference on Parallel Processing, pages 304–315. Springer.
Harter, T., Salmon, B., Liu, R., Arpaci-Dusseau, A. C., and Arpaci-Dusseau, R. H. (2016). Slacker: Fast distribution with lazy docker containers. In 14th USENIX Conference on File and Storage Technologies (FAST 16), pages 181–195.
Ismail, B. I., Goortani, E. M., Ab Karim, M. B., Tat, W. M., Setapa, S., Luke, J. Y., and Hoe, O. H. (2015). Evaluation of docker as edge computing platform. In 2015 IEEE conference on open systems (ICOS), pages 130–135. IEEE.
Ismail, L. and Materwala, H. (2021). Escove: energy-sla-aware edge–cloud computation offloading in vehicular networks. Sensors, 21(15):5233.
Kangjin, W., Yong, Y., Ying, L., Hanmei, L., and Lin, M. (2017). Fid: A faster image distribution system for docker platform. In 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS* W), pages 191–198. IEEE.
Klas, G. (2017). Edge computing and the role of cellular networks. Computer, 50(10):40–49.
Knob, L. A. D., Faticanti, F., Ferreto, T., and Siracusa, D. (2021). Community-based placement of registries to speed up application deployment on edge computing. In 2021 IEEE International Conference on Cloud Engineering (IC2E), pages 147–153. IEEE.
Liang, M., Shen, S., Li, D., Mi, H., and Liu, F. (2016). Hdid: An efficient hybrid docker image distribution system for datacenters. In National Software Application Conference, pages 179–194. Springer.
Luo, Q., Hu, S., Li, C., Li, G., and Shi, W. (2021). Resource scheduling in edge computing: A survey. IEEE Communications Surveys & Tutorials, 23(4):2131–2165.
MacQueen, J. (1967). Classification and analysis of multivariate observations. In Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability, pages 281–297.
Mansouri, Y. and Babar, M. A. (2021). A review of edge computing: Features and resource virtualization. Journal of Parallel and Distributed Computing, 150:155–183.
Mao, Y., You, C., Zhang, J., Huang, K., and Letaief, K. B. (2017). A survey on mobile edge computing: The communication perspective. IEEE communications surveys & tutorials, 19(4):2322–2358.
Merkel, D. et al. (2014). Docker: lightweight linux containers for consistent development and deployment. Linux j, 239(2):2.
Rejiba, Z., Masip-Bruin, X., and Marín-Tordera, E. (2019). A survey on mobility-induced service migration in the fog, edge, and related computing paradigms. ACM Computing Surveys (CSUR), 52(5):1–33.
Satyanarayanan, M. (2017). The emergence of edge computing. Computer, 50(1):30–39.
Satyanarayanan, M., Bahl, P., Caceres, R., and Davies, N. (2009). The case for vm-based cloudlets in mobile computing. IEEE pervasive Computing, 8(4):14–23.
Souza, P., Kayser, C., Roges, L., and Ferreto, T. (2023a). Thea-a qos, privacy, and power-aware algorithm for placing applications on federated edges. In 2023 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pages 136–143. IEEE.
Souza, P. S., Ferreto, T., and Calheiros, R. N. (2023b). Edgesimpy: Python-based modeling and simulation of edge computing resource management policies. Future Generation Computer Systems.
Uber (2022). uber/kraken: P2p docker registry capable of distributing tbs of data in seconds.
Yao, H., Bai, C., Zeng, D., Liang, Q., and Fan, Y. (2015). Migrate or not? exploring virtual machine migration in roadside cloudlet-based vehicular cloud. Concurrency and Computation: Practice and Experience, 27(18):5780–5792.
Publicado
17/10/2023
Como Citar
ROGES, Lucas; FERRETO, Tiago.
Dynamic Provisioning of Container Registries in Edge Computing Infrastructures. In: SIMPÓSIO EM SISTEMAS COMPUTACIONAIS DE ALTO DESEMPENHO (SSCAD), 24. , 2023, Porto Alegre/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 85-96.
DOI: https://doi.org/10.5753/wscad.2023.235933.
