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Machine Learning Aided Orchestration in Multi-Tenant Networks
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Optical Network Laboratory (ON Lab).
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Optical Network Laboratory (ON Lab).
Deutsche Bahn AG, Germany.
Ericsson Research, Kista, Sweden.
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2018 (English)In: IEEE Photonics Society Summer Topicals Meeting Series, SUM 2018, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 125-126Conference paper, Published paper (Refereed)
Abstract [en]

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. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2018. p. 125-126
Keywords [en]
Multi tenants, Network infrastructure, Network slicing, Reinforcement learning
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-236704DOI: 10.1109/PHOSST.2018.8456735ISI: 000455155000054Scopus ID: 2-s2.0-85054171914ISBN: 9781538653432 (print)OAI: oai:DiVA.org:kth-236704DiVA, id: diva2:1262436
Conference
2018 IEEE Photonics Society Summer Topicals Meeting Series, SUM 2018, 9 July 2018 through 11 July 2018
Funder
Vinnova, 671636
Note

Conference code: 139363; Export Date: 22 October 2018; Conference Paper; Funding details: K5; Funding details: 671636, VINNOVA; Funding text: This work was developed while Ahmad Rostami was with Ericsson Research. The work described in this paper was carried out with the support of the Kista 5G Transport Lab (K5) project funded by VINNOVA and Ericsson, and of the H2020-ICT-2014 project 5GEx (Grant Agreement no. 671636). QC 20181112

Available from: 2018-11-12 Created: 2018-11-12 Last updated: 2019-04-05Bibliographically approved

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Natalino, CarlosRaza, Muhammad RehanWosinska, LenaMonti, Paolo

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