Jacopo Massa

• PhD Student at University of Pisa

This work investigates the data-aware multi-service application placement problem in Cloud-Edge settings. We previously introduced EdgeWise, a hybrid approach that combines declarative programming with Mixed-Integer Linear Programming (MILP) to determine optimal placements that minimise operational costs and unnecessary data transfers. The declarat...

Cloud-Edge applications like industrial control systems and connected vehicles demand stringent end-to-end latency guarantees. Among existing data plane candidate solutions for bounded latency networking, the guaranteed Latency-Based Forwarding (gLBF) approach ensures punctual delivery of traffic flows by managing per-hop delays to meet specific la...

The Cloud-Edge continuum enhances application performance by bringing computation closer to data sources. However, it presents considerable challenges in managing resources and determining service placement, as these tasks require navigating diverse, dynamic environments characterised by fluctuating network conditions. Addressing these challenges c...

With the widespread adoption of the Internet of Things (IoT), billions of devices are now connected to the Internet and can reach computing facilities along the Cloud-IoT continuum to process the data they produce. This has led to a dramatic increase in the amount of deployed IoT-based applications as well as the data they need to crunch. Those app...

We present a declarative solution to determine, in a data-aware manner, application service placements and SDN data routings over Cloud-IoT infrastructures while meeting functional (software, hardware, IoT) and non-functional (security, latency, bandwidth) application requirements. The solution employs continuous reasoning to speed up the reconfigu...