Avaliação de Disponibilidade de uma Arquitetura de Computação de Borda com Redes de Petri Estocásticas
Mobile Edge Computing (MEC) emerged as an alternative to reduce network latency by bringing the data processing close to the users. This proximity requires that the service is available most of the time. Trying to assess the availability of such systems in real contexts requires high costs. This paper uses Stochastic Petri Nets (SPNs) to assess the availability of an MEC architecture, seeking to avoid premature investment in real equipment. In addition, this work presents a sensitivity analysis that identifies the most critical components of architecture. This work has the potential to assist administrators in redefining the most optimized MEC architectures by decreasing the risk of failure.
Araujo, J., Silva, B., Oliveira, D., and Maciel, P. (2014). Dependability evaluation of a mhealth system using a mobile cloud infrastructure. In 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages 1348–1353. IEEE.
Bris, R. (2013). Evaluation of the production availability of an offshore installation bystochastic petri nets modeling. In The International Conference on Digital Technologies 2013, pages 147–155. IEEE.
da Silva Lisboa, M. F. F., Santos, G. L., Lynn, T., Sadok, D., Kelner, J., Endo, P. T., et al.(2018). Modeling the availability of an e-health system integrated with edge, fog and cloud infrastructures. In 2018 IEEE Symposium on Computers and Communications(ISCC), pages 00416–00421. IEEE.
Guo, J., Luo, W., Song, B., Yu, F. R., and Du, X. (2020). Intelligence-sharing vehicular networks with mobile edge computing and spatio temporal knowledge transfer. IEEE Network.
Oliveira, D., Araujo, J., Matos, R., and Maciel, P. (2013). Availability and energy consumption analysis of mobile cloud environments. In 2013 IEEE International Conference on Systems, Man, and Cybernetics, pages 4086–4091. IEEE.
Santos, G. L., Endo, P. T., da Silva Lisboa, M. F. F., da Silva, L. G. F., Sadok, D., Kelner,J., Lynn, T., et al. (2018). Analyzing the availability and performance of an e-health system integrated with edge, fog and cloud infrastructures. Journal of Cloud Computing, 7(1):16.
Silva, B., Matos, R., Callou, G., Figueiredo, J., Oliveira, D., Ferreira, J., Dantas, J.,Lobo, A., Alves, V., and Maciel, P. (2015a). Mercury: An integrated environmentfor performance and dependability evaluation of general systems. In Proceedings of Industrial Track at 45th Dependable Systems and Networks Conference, DSN.
Silva, F. A., Rodrigues, M., Maciel, P., Kosta, S., and Mei, A. (2015b). Planning mobile cloud infrastructures using stochastic petri nets and graphic processing units. In 2015 IEEE 7th International Conference on Cloud Computing Technology and Science(CloudCom), pages 471–474. IEEE.
Trinh, C. and Yao, L. (2017). Energy-aware mobile edge computing for low-latency visual data processing. pages 128–133.
Wan, S., Gu, Z., and Ni, Q. (2020). Cognitive computing and wireless communicationson the edge for healthcare service robots. Computer Communications, 149:99–106.
Yuan, L. and Meng, X.-Y. (2011). Reliability analysis of a warm standby repairable system with priority in use. Applied Mathematical Modelling, 35(9):4295–4303.
Zafari, F., Leung, K. K., Towsley, D., Basu, P., Swami, A., and Li, J. (2020). Let’sshare: A game-theoretic framework for resource sharing in mobile edge clouds. arXivpreprint arXiv:2001.00567.