Author:
Shang Fangjian,Li Xin,Zhai Di,Lu Yang,Zhang Dong Lei,Yuwen Qian
Abstract
Abstract
To allocate the network slice optimally, a two-phase optimal allocation approach is proposed to assign the network slices with users. First, the network slice allocation system in the core cloud network is modeled as a Markov process, and then the deep reinforcement learn is adopted to allocate the network slices. In the second phase, we formulate the network slice allocation problem as Lagrange multipliers problem. The iteration method is designed to achieve the optimization problem. Numerical results demonstrate that the proposed approach can allocate the network slices at a high efficiency.
Subject
General Physics and Astronomy
Reference13 articles.
1. Radio resource management techniques for eMBB and mMTC services in 5G dense small cell scenarios;Ahmood,2016
2. A Workflow-Aided Internet of Things Paradigm with Intelligent Edge Computing;Qian
3. A Novel QoS Framework for Network Slicing in 5G and Beyond Networks Based on SDN and NFV;Shu;IEEE Network,2020
4. On radio access network slicing from a radio resource management perspective;Salient;IEEE Wireless Communications,2017
5. Slicing the edge: resource allocation for RAN network slicing;Vo;IEEE Wireless Communications Letters,2018
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