Abstract
This paper introduces an intelligent network service orchestration platform, referred to as 5G-VIOS for 5G networks and beyond in accordance with the Zero-touch Network and Service Management (ZSM) paradigm. The proposed solution is responsible for an automated network slicing and life-cycle management of network applications and services, across multiple administrative and technological domains. An Artificial Intelligent (AI) model utilising Machine Learning (ML) techniques is exploited to intelligently and efficiently profile the network services and predict the efficient configuration of resources needed to meet the performance targets and Service Level Agreements (SLAs) of these network services across multiple domains. We test and validate the performance of the prediction models for both resource configuration and utilisation in various settings for different resources and data rates. We also showcase how resource utilisation predictions of a virtualised network service can significantly assist in its life cycle management by proactively preventing unnecessary actions such as its migration
Original language | English |
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Article number | 110202 |
Number of pages | 12 |
Journal | Computer Networks |
Volume | 241 |
Early online date | 30 Jan 2024 |
DOIs | |
Publication status | Published - 1 Mar 2024 |
Bibliographical note
Funding Information:This work received funding from UK funded Project REASON under the FONRC sponsored DSIT , and EU project 5G-VICTORI (grant agreement No. 857201 ).
Publisher Copyright:
© 2024 Elsevier B.V.
Keywords
- Cross-domain orchestration
- VNF profiling
- Resource minimising