projects

Intent-based Compute Continuum

The rise of IoT has increased the need for scalable storage and processing, leading to the compute continuum, which integrates edge and cloud resources. However, testing applications in such environments is challenging due to complex networks, resource heterogeneity, and high costs associated with real-world experimentation. While simulation toolkits help, they often lack accuracy, particularly in modeling dynamic network interactions. Emulation, which more closely mimics real-world conditions, provides a more reliable alternative but is often limited to specific functions.

Cloud Data Centre Digital Twin

As demand for data processing grows, cloud data centres have become essential but remain complex to manage, especially in maintenance and resource allocation. This project proposes a Digital Twin—a 3D, real-time visualization and monitoring tool that integrates data from OpenStack APIs and infrastructure devices to represent VMs, hypervisors, and physical servers. Our findings show that the Digital Twin improves monitoring and management efficiency, paving the way for more usable and effective data centre operations.

Greening Edge Data Centres

The growing energy demand and carbon footprint of Edge Data Centres pose urgent challenges. Reducing reliance on brown energy while integrating renewable sources is essential, yet their intermittency makes efficient use difficult. This project proposes novel frameworks for resource management and scheduling that maximize renewable energy utilization through advanced optimization. Central to these frameworks is load shaping with adaptive Quality of Service (QoS), enabling dynamic QoS adjustments and resource autoscaling based on renewable energy availability.