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Safeguard Network Slicing in 5G: A Learning Augmented Optimization Approach
- Source :
- IEEE Journal on Selected Areas in Communications. 38:1600-1613
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- Network slicing, as a key 5G enabling technology, is promising to support with more flexibility, agility, and intelligence towards the provisioned services and infrastructure management. Fulfilling these tasks is challenging, as nowadays networks are increasingly heterogeneous, dynamic and large-dimensioned. This contradicts the dominant network slicing solutions that only customize immediate performance over one snapshot of the system in the literature. Instead, this paper first presents a two-stage slicing optimization model with time-averaged metrics to safeguard the network slicing in the dynamical networks, where prior environmental knowledge is absent but can be partially observed at runtime. Directly solving an off-line solution to this problem is intractable since the future system realizations are unknown before decisions. Therefore, we propose a learning augmented optimization approach with deep learning and Lyapunov stability theories. This enables the system to learn a safe slicing solution from both historical records and run-time observations. We prove that the proposed solution is always feasible and nearly optimal, up to a constant additive factor. Finally, we demonstrate up to $2.6\times $ improvement in the simulation when compared with three state-of-the-art algorithms.
- Subjects :
- Computer Networks and Communications
business.industry
Computer science
Deep learning
Distributed computing
Knowledge engineering
020206 networking & telecommunications
Provisioning
Lyapunov optimization
02 engineering and technology
Slicing
Safeguard
0202 electrical engineering, electronic engineering, information engineering
Artificial intelligence
Electrical and Electronic Engineering
business
5G
Subjects
Details
- ISSN :
- 15580008 and 07338716
- Volume :
- 38
- Database :
- OpenAIRE
- Journal :
- IEEE Journal on Selected Areas in Communications
- Accession number :
- edsair.doi...........d425e44b0e2a522994f9caf34ec28409