Year: 2023
Type: article
Abstract: For a network slice that spans multiple technology and/or administrative domains, these domains must ensure that the slice’s End-to-End (E2E) Service Level Agreement (SLA) is met. Thus, the E2E SLA should be decomposed to partial SLAs, assigned to each of these domains. Assuming a two-level management architecture consisting of an E2E service orchestrator and local domain controllers, we consider that the former is only aware of historical data of the local controllers’ responses to previous slice requests, and captures this knowledge in a risk model per domain. In this study, we propose the use of Neural Network (NN) based risk models, using such historical data, to decompose the E2E SLA. Specifically, we introduce models that incorporate monotonicity, applicable even in cases involving small datasets. An empirical study on a synthetic multi-domain dataset demonstrates the efficiency of our approach.
Source: IEEE Networking Letters
Institutions: University of Amsterdam, Nokia (Belgium)
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: European Commission
OpenAlex ID: W4386280781