A Heuristically Assisted Deep Reinforcement Learning Approach for Network Slice Placement

Network Slice placement with the problem of allocation of resources from a virtualized substrate network is an optimization problem which can be formulated as a multi-objective Integer Linear Programming (ILP) problem. However, to cope with the complexity of such a continuous task and seeking for op...

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Veröffentlicht in:	IEEE eTransactions on network and service management Jg. 19; H. 4; S. 4794 - 4806
Hauptverfasser:	Alves Esteves, Jose Jurandir, Boubendir, Amina, Guillemin, Fabrice, Sens, Pierre
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.12.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms automation Bandwidth Computer Science Convergence Deep learning deep reinforcement learning Feature extraction Integer programming large scale Linear programming Machine learning Network slicing Networking and Internet Architecture Optimization Placement Random access memory Reinforcement learning Substrates Training Automation Deep Reinforcement Learning Placement Large Scale Optimization Network Slicing
ISSN:	1932-4537, 1932-4537
Online-Zugang:	Volltext
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