CAONS: Controle de Admissão On-line para RAN Slicing Baseado na Convergência de Comunicação e Computação
Abstract
The deployment of 5G mobile networks has leveraged Network Slicing (NS), a disruptive technology that can provide dedicated resources in mobile systems, helping to monetize the physical and logical infrastructure. However, NS creates new challenges, such as (1) dynamic and flexible management of Radio Access Network (RAN) resources, (2) smooth integration of services in Multi Access Edge Computing (MEC), and (3) admission of new tenants to the network. In this work, we propose an admission control algorithm aware of RAN resources, which uses the overbooking technique to increase infrastructure utilization, penalizing the operator in case of violations. We evaluate the model and compare it with known solutions, using data from different applications.
References
Bega, D. et al. (2019). A machine learning approach to 5G infrastructure market optimization. IEEE Transactions on Mobile Computing, 19(3):498-512.
Black, P. E. (2005). Greedy algorithm. Dictionary of Algorithms and Data Structures, 2:62.
Chen, G., Liew, S. C., and Shao, Y. (2022). Uncertainty-of-information scheduling: A restless multi-armed bandit framework. IEEE Transactions on Information Theory.
Cominardi, L., Deiss, T., Filippou, M., Sciancalepore, V., Giust, F., and Sabella, D. (2020). Mec support for network slicing: Status and limitations from a standardization viewpoint. IEEE Communications Standards Magazine, 4(2):22-30.
Elayoubi, S. E. et al. (2019). 5G RAN slicing for verticals: Enablers and challenges. IEEE Communications Magazine, 57:28-34.
Gao, Z., Han, Y., Ren, Z., and Zhou, Z. (2019). Batched multi-armed bandits problem. Advances in Neural Information Processing Systems, 32.
Garivier, A. and Cappé, O. (2011). The kl-ucb algorithm for bounded stochastic bandits and beyond. In Kakade, S. M. and von Luxburg, U., editors, Proceedings of the 24th Annual Conference on Learning Theory, volume 19 of Proceedings of Machine Learning Research, pages 359-376, Budapest, Hungary. PMLR.
Guan, Z., Ji, K., Bucci Jr, D. J., Hu, T. Y., Palombo, J., Liston, M., and Liang, Y. (2020). Robust stochastic bandit algorithms under probabilistic unbounded adversarial attack. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 34, pages 4036-4043.
Hwang, S. and Park, S. (2017). On the effects of resource usage ratio on data rate in LTE systems. In 2017 19th International Conference on Advanced Communication Technology (ICACT), pages 78-80.
Li, F., Yu, D., Yang, H., Yu, J., Karl, H., and Cheng, X. (2020). Multi-armed-bandit-based spectrum scheduling algorithms in wireless networks: A survey. IEEE Wireless Communications, 27(1):24-30.
Li, R. et al. (2018a). Deep reinforcement learning for resource management in network slicing. IEEE Access, 6:74429-74441.
Li, Z., Uusitalo, M. A., Shariatmadari, H., and Singh, B. (2018b). 5G urllc: Design challenges and system concepts. In 2018 15th international symposium on wireless communication systems (ISWCS), pages 1-6. IEEE.
Lima, H. V., Bruno, G. Z., Grings, F. H., Both, C. B., Alberti, A. M., Cardoso, K. V., and Correa, S. L. (2022). Controle de admissão para network slicing ciente de recursos de rede e de processamento.
Mahajan, A. and Teneketzis, D. (2008). Multi-armed bandit problems. In Foundations and applications of sensor management, pages 121-151. Springer.
Malandrino, F. et al. (2020). From megabits to cpu ticks: Enriching a demand trace in the age of mec. IEEE Transactions on Big Data, 6(1):43-50.
Ontanón, S. (2013). The combinatorial multi-armed bandit problem and its application to real-time strategy games. In Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, volume 9.
Rifai, B. and Supriyanto, E. (2017). Management system failover dengan routing dinamis open shortest path first dan border gateway protocol. Jurnal Ilmu Pengetahuan dan Teknologi Komputer, 3:39-46.
Sciancalepore, V., Zanzi, L., Costa-Perez, X., and Capone, A. (2021). Onets: online network slice broker from theory to practice. IEEE Transactions on Wireless Communications, 21(1):121-134.
Weisbecker, F. (2013). Status of Linux dynticks. In 9th annual workshop on Operating Systems Platforms for Embedded Real-Time applications.
Zhang, S. (2019). An overview of network slicing for 5G. IEEE Wireless Communications, 26(3):111-117.
