Recent medical applications are largely dominated by the application of Machine Learning
(ML) models to assist expert decisions, leading to disruptive innovations in radiology …

The edge computing paradigm allows computationally intensive tasks to be offloaded from
small devices to nearby (more) powerful servers, via an edge network. The intersection …

Telepathology aims to replace the pathology operations performed on-site, but current
systems are limited by their prohibitive cost, or by the adopted underlying technologies. In …

The Internet of Things (IoT), coupled with the edge computing paradigm, is enabling several
pervasive networked applications with stringent real-time requirements, such as …

Blockchain and edge computing have been widely applied in video streaming systems.
However, previous works lack a joint consideration of video redundancy and full utilization of …

The demand of low latency applications has fostered interest in edge computing, a recent
paradigm in which data is processed locally, at the edge of the network. The challenge of …

Internet traffic matrices are used nowadays for a variety of network management operations,
from planning to repairing. Despite years of research on the topic, obtaining a global view of …

In recent years, containerized deployment models have gained favor across many domain of
applications. Kubernetes, the de-facto standard for containers orchestration, can efficiently …

The soaring complexity of networks has led to more and more complex methods to manage
and orchestrate efficiently the multitude of network environments. Several solutions exist …

The high programmability provided by Software Defined Networking (SDN) paradigm
facilitated the integration of Machine Learning (ML) methods to design a new family of …