Edge artificial intelligence (AI) is an innovative computing paradigm that aims to shift the
training and inference of machine learning models to the edge of the network. This paradigm …

The edge–cloud continuum combines heterogeneous resources, which are complex to
manage. Serverless edge computing is a suitable candidate to manage the continuum by …

Quantum processing units (QPUs) are currently exclusively available from cloud vendors.
However, with recent advancements, hosting QPUs will soon be possible everywhere …

Serverless computing has ushered in a transformative paradigm, with a promise to alleviate
developers from the intricacies of infrastructure management. However, current serverless …

In the realm of edge intelligence, emerging video analytics applications are often based on
resource constrained edge devices. These applications need systems which are able to …

Nowadays, modern service compositions are increasingly adopted in critical scenarios
where advanced Quality of Services (QoS) such as low latency, security, and privacy are …

Serverless Computing is a computing paradigm that provides efficient infrastructure
management and elastic scalability. Serverless functions scale up or down based on …

In this work, we tackle the problem of performing multi-label classification in the case of
extremely heterogeneous data and with decentralized Machine Learning. Solving this issue …

Scheduling workloads on large-scale infrastructures, such as in the Edge-Cloud continuum
is a challenging task. Usually, the scheduling algorithm considers only a limited sample of …

Serverless Computing brings advantages to the Edge-Cloud contin-uum, like simplified
programming and infrastructure management. In composed workflows, where serverless …