Pierangelo Di Sanzo

Proactive Scalability and Management of Resources in Hybrid Clouds via Machine Learning

2015

In this paper, we present a novel framework for supporting the management and optimization of application subject to software anomalies and deployed on large scale cloud architectures, composed of different geographically distributed cloud regions. The …

A Bootstrapping Technique for Reducing the Costs of Machine Learning Models for Predicting Execution Times in IaaS Clouds

2025

Machine Learning (ML) emerged as a powerful tool for predicting task execution times across the variety of VM types offered by Infrastructure-as-a-Service (IaaS) clouds. However, training ML models to ensure accurate predictions can often become …