The rapidly evolving landscape of critical communications infrastructure is characterized by the integration of advanced technologies and the growing demand for efficient systems. Industrial Internet of Things (IoT) systems in smart grids are at the forefront of this transformation, promising improved energy distribution and management. This research focuses on ensuring Service Level Agreement (SLA) compliance of distributed software systems, which are critical to critical communication infrastructures. Research objectives include contextualization of critical communication infrastructure and industrial IoT in smart grids. It evaluates redundancy and software deployment patterns in industrial IoT software development, including continuous integration and continuous delivery (CI/CD) practices. It also explores observability data in running systems for predictive maintenance, applying deep learning and machine learning for automated fault management and autoscaling in computer clusters.

The rapidly evolving landscape of critical communications infrastructure is characterized by the integration of advanced technologies and the growing demand for efficient systems. Industrial Internet of Things (IoT) systems in smart grids are at the forefront of this transformation, promising improved energy distribution and management. This research focuses on ensuring Service Level Agreement (SLA) compliance of distributed software systems, which are critical to critical communication infrastructures. Research objectives include contextualization of critical communication infrastructure and industrial IoT in smart grids. It evaluates redundancy and software deployment patterns in industrial IoT software development, including continuous integration and continuous delivery (CI/CD) practices. It also explores observability data in running systems for predictive maintenance, applying deep learning and machine learning for automated fault management and autoscaling in computer clusters.

Ensuring Service Level Agreement Compliance for smart grid communications

GREGGIO, NICOLA
2023/2024

Abstract

The rapidly evolving landscape of critical communications infrastructure is characterized by the integration of advanced technologies and the growing demand for efficient systems. Industrial Internet of Things (IoT) systems in smart grids are at the forefront of this transformation, promising improved energy distribution and management. This research focuses on ensuring Service Level Agreement (SLA) compliance of distributed software systems, which are critical to critical communication infrastructures. Research objectives include contextualization of critical communication infrastructure and industrial IoT in smart grids. It evaluates redundancy and software deployment patterns in industrial IoT software development, including continuous integration and continuous delivery (CI/CD) practices. It also explores observability data in running systems for predictive maintenance, applying deep learning and machine learning for automated fault management and autoscaling in computer clusters.
2023
Ensuring Service Level Agreement Compliance for smart grid communications
The rapidly evolving landscape of critical communications infrastructure is characterized by the integration of advanced technologies and the growing demand for efficient systems. Industrial Internet of Things (IoT) systems in smart grids are at the forefront of this transformation, promising improved energy distribution and management. This research focuses on ensuring Service Level Agreement (SLA) compliance of distributed software systems, which are critical to critical communication infrastructures. Research objectives include contextualization of critical communication infrastructure and industrial IoT in smart grids. It evaluates redundancy and software deployment patterns in industrial IoT software development, including continuous integration and continuous delivery (CI/CD) practices. It also explores observability data in running systems for predictive maintenance, applying deep learning and machine learning for automated fault management and autoscaling in computer clusters.
Cloud
Networks
Infrastructure
Internet of Things
Monitoring
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/64046