XAI-Guided Optimization of a Multilayer Network Regression Model

The recent technological advances create increased network capacity demand, highlighting the need for new network optimization methods. However, the proposed solutions require broad testing with numerous time-consuming simulations. Thus, estimation methods based on Machine Learning (ML) are develope...

Full description

Saved in:
Bibliographic Details
Main Authors: Duszynska, Katarzyna, Polski, Pawel, Wlosek, Micha, Knapinska, Aleksandra, Lechowicz, Piotr, Walkowiak, Krzysztof
Format: Conference Proceeding
Language:English
Subjects:
Explainable AI
explainable artificial intelligence
machine learning
Measurement
multilayer network
Nonhomogeneous media
Optimization methods
Predictive models
resource allocation
Runtime
Uncertainty
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The recent technological advances create increased network capacity demand, highlighting the need for new network optimization methods. However, the proposed solutions require broad testing with numerous time-consuming simulations. Thus, estimation methods based on Machine Learning (ML) are developed to improve this process. In this work, we create a regression network model to predict four resource utilization metrics using the input set of connection requests. Using eXplainable Artificial Intelligence (XAI) tools, we optimize the proposed model for faster inference without a decrease in prediction quality.
ISSN:1861-2288
DOI:10.23919/IFIPNetworking62109.2024.10619785