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Title: The NECOS Approach to End-to-End Cloud-Network Slicing as a Service
Authors: Clayman, Stuart
Neto, Augusto Venancio
Verdi, Fabio L.
Correa, Sand L.
Sampaio, Silvio
Sakellariou, Ilias
Mamatas, Lefteris
Pasquini, Rafael
Cardoso, Kleber V.
Tusa, Francesco
Rothenberg, Christian
Serrat, Joan
Type: Article
Subjects: FRASCATI::Natural sciences::Computer and information sciences
Keywords: Network slicing
Cloud computing
Data centers
Machine learning
Issue Date: Mar-2021
Source: IEEE Communications Magazine
Volume: 59
Issue: 3
First Page: 91
Last Page: 97
Abstract: Cloud-network slicing is a promising approach to serve vertical industries delivering their services over multiple administrative and technological domains. However, there are numerous open challenges to provide end-to-end slices due to complex business and engineering requirements from service and resource providers. This article presents a reference architecture for the cloud-network slicing concept and the practical realization of the slice-as-a-service paradigm, which are key results from the Novel Enablers in Cloud Slicing (NECOS) project. The NECOS platform has been designed to consider modularity, separation of concerns, and multi-domain dynamic operation as prime attributes. The architecture comprises a set of interworking components to automatically create, manage, and decommission end-to-end cloud-network slice instances in a lightweight manner. NECOS orchestrates slices at runtime, spanning across core/edge data centers and wired/wireless network infrastructures. The novelties of the multi-domain NECOS platform are validated through three proof-of-concept experiments: (i) a touristic content delivery service slice deployment featuring on-demand virtual infrastructure management across three countries on different continents to meet particular slice requirements; (ii) intelligent slice elasticity driven by machine learning techniques; and (iii) market-place-based resource discovery capabilities.
ISSN: 0163-6804
Other Identifiers: 10.1109/MCOM.001.2000702
Appears in Collections:Department of Applied Informatics

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