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AZTEC: Anticipatory Capacity Allocation for Zero-Touch Network Slicing

Bega, Dario and Gramaglia, Marco and Fiore, Marco and Banchs, Albert and Costa-Perez, Xavier (2020) AZTEC: Anticipatory Capacity Allocation for Zero-Touch Network Slicing. In: IEEE International Conference on Computer Communications (INFOCOM 2020), July 6-9, 2020, Online (previously Toronto, Canada).

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Abstract

The combination of network softwarization with network slicing enables the provisioning of very diverse services over the same network infrastructure. However, it also creates a complex environment where the orchestration of network resources cannot be guided by traditional, human-in-the-loop network management approaches. New solutions that perform these tasks automatically and in advance are needed, paving the way to zero-touch network slicing. In this paper, we propose AZTEC, a data- driven framework that effectively allocates capacity to individual slices by adopting an original multi-timescale forecasting model. Hinging on a combination of Deep Learning architectures and a traditional optimization algorithm, AZTEC anticipates resource assignments that minimize the comprehensive management costs induced by resource overprovisioning, instantiation and reconfiguration, as well as by denied traffic demands. Experiments with real-world mobile data traffic show that AZTEC dynamically adapts to traffic fluctuations, and largely outperforms state-of-the-art solutions for network resource orchestration.

Item Type: Conference or Workshop Papers (Paper)
Subjects: UNSPECIFIED
Divisions: UNSPECIFIED
Depositing User: Marco Fiore
Date Deposited: 08 Jul 2020 06:22
Last Modified: 08 Jul 2020 06:22
URI: http://eprints.networks.imdea.org/id/eprint/2161

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