Machine Learning Aided Orchestration in Multi-tenant Networks

被引：0
|
作者：
Natalino, Carlos [1 ]
Raza, Muhammad Rehan [1 ]
Rostami, Ahmad [2 ]
Ohlen, Peter [3 ]
Wosinska, Lena [1 ]
Monti, Paolo [1 ]
机构：
[1] KTH Royal Inst Technol, Kista, Sweden
[2] Deutsch Bahn AG, Berlin, Germany
[3] Ericsson Res, Kista, Sweden
来源：
2018 IEEE PHOTONICS SOCIETY SUMMER TOPICAL MEETING SERIES (SUM) | 2018年
基金：
欧盟地平线“2020”;
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Software Defined Networking enables the efficient sharing of a network infrastructure among different tenants, a concept known as network slicing. The paper presents a slicing strategy based on reinforcement learning able to efficiently orchestrate services requested by mobile and cloud tenants.
引用
收藏
页码：125 / 126
页数：2
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