Survey on Machine Learning-Enabled Network Slicing: Covering the Entire Life Cycle

Abstract

Network slicing (NS) is becoming an essential element of service management and orchestration in communication networks, starting from mobile cellular networks and extending to a global initiative. NS can reshape the deployment and operation of traditional services, support the introduction of new ones, vastly advance how resource allocation performs in networks, and notably change the user experience. Most of these promises still need to reach the real world, but they have already demonstrated their capabilities in many experimental infrastructures. However, complexity, scale, and dynamism are pressuring for a Machine Learning (ML)-enabled NS approach in which autonomy and efficiency are critical features. This trend is relatively new but growing fast and attracting much attention. This article surveys Artificial Intelligence-enabled NS and its potential use in current and future infrastructures. We have covered state-of-the-art ML-enabled NS for all network segments and organized the literature according to the phases of the NS life cycle. We also discuss challenges and opportunities in research on this topic.

Authors

Adnei Donatti, Department of Computer Engineering and Digital Systems, University of São Paulo, São Paulo, Brazil

Sand L. Corrêa, Institute of Informatics, Federal University of Goiás, Goiânia, Brazil

Joberto S. B. Martins, Computer Science Department, Salvador University, Salvador, Brazil

Antonio J. G. Abelem, Computer Science Department, Federal University of Pará, Belém, Brazil

Cristiano Bonato Both, PPGCA, UNISINOS, São Leopoldo, Brazil

Flávio de Oliveira Silva, Faculty of Computing, Federal University of Uberlândia, Uberlândia, Brazil

José A. Suruagy, Informatics Center, Federal University of Pernambuco, Recife, Brazil

Rafael Pasquini, Faculty of Computing, Federal University of Uberlândia, Uberlândia, Brazil

Rodrigo Moreira, Institute of Exact and Technological Sciences, Federal University of Viçosa, Viçosa, Brazil

Kleber V. Cardoso, Institute of Informatics, Federal University of Goiás, Goiânia, Brazil

Tereza C. Carvalho, Department of Computer Engineering and Digital Systems, University of São Paulo, São Paulo, Brazil