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A Conformal Prediction-Based Framework for CPU Load Forecasting: A Black-Box Approach

Fulltext:


Authors:

Edin Jelačić, Cristina Seceleanu, Peter Backeman, Ning Xiong, Tiberiu Seceleanu, Axel Jantsch

Research groups:

Formal Modelling and Analysis of Embedded Systems
Model-Based Engineering of Embedded Systems

Publication Type:

Conference/Workshop Paper

Venue:

49th IEEE International Conference on Computers, Software, and Applications

Abstract

To address safety concerns in industrial systems, we propose a framework for forecasting CPU load with respect to a predetermined threshold, allowing customers to add tasks from a predefined library. Existing tools, akin to Windows Task Manager, provide limited insights due to their aggregate nature and high computational overhead. Our approach uses conformal prediction for rapid uncertainty-aware forecasts and Shapley value analysis to quantify individual task contributions to the CPU load. This proof-of-concept framework improves system safety assessment by addressing key research questions in load prediction and validation, paving the way for refined measurement methodologies in industrial applications.

Bibtex

@inproceedings{Jelačić7351,
author = {Edin Jelačić and Cristina Seceleanu and Peter Backeman and Ning Xiong and Tiberiu Seceleanu and Axel Jantsch},
title = {A Conformal Prediction-Based Framework for CPU Load Forecasting: A Black-Box Approach},
month = {July},
year = {2025},
booktitle = {49th IEEE International Conference on Computers, Software, and Applications},
url = {http://www.es.mdu.se/publications/7351-}
}