Resource Adjustment Based on Deep Reinforcement Learning for Network Slices with Priority Classes

Yuji KAMEYAMA; Takuji TACHIBANA

Summary

International Conference on Emerging Technologies for Communications

2020

Session Number:P2

Session:

Number:P2-2

Resource Adjustment Based on Deep Reinforcement Learning for Network Slices with Priority Classes

Yuji KAMEYAMA, Takuji TACHIBANA,

pp.-

Publication Date:2020/12/2

Online ISSN:2188-5079

DOI:10.34385/proc.63.P2-2

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Summary:

In this paper, for network slices with di?erent priority classes, we propose a resource adjustment based on deep reinforcement learning. We evaluate the proposed method and show its e?ectiveness by comparing with constant adjustment method.