DIQIP
Device-Independent Quantum Information Processing represents a new paradigm for quantum information processing: the goal is to design protocols to solve relevant information tasks without relying on any assumption on the devices used in the
DISEDAN
The DISEDAN project proposes an evolutionary solution to enhance the content delivery via Internet. It focuses on research in the area of multi-criteria content source (server) selection, considering user and server contexts and requested
DIVIDEND
Our world is in the midst of a “big data” revolution, driven by the ubiquitous ability to gather, analyse, and query datasets of unprecedented variety and size. The sheer storage volume and processing capacity required to manage these
DRUID-NET
The potential offered by the abundance of sensors, actuators and communications in IoT era is hindered by the limited computational capacity of local nodes, making the distribution of computing in time and space a necessity. Several key
DYPOSIT
The DYPOSIT project tackles the problem of large, shared CPS infrastructures under attack. In particular, the project responds to the critical need for dynamically formulating and adapting security policies, rapidly and on-demand, in the
E-CROPS
“Anytime, anywhere, anything” has been the recent catch-phrase used by technology evangelists promising untethered wireless data flow not only among people, but also among devices of any imaginable sort. Trillions of autonomous devices are
ECOMOME
The energy consumption of mobile networks has been the source of animated debates in the recent period, with the deployment of 5G technologies. However, the energy consumption estimations put forward by the different parties in the debate
eGlasses
The eGlasses project is focused on the development of an open platform in the form of multisensory electronic glasses and on the integration and designing of new intelligent interaction methods using the eGlasses platform. This is an
EXPECTATION
Explainable AI (XAI) has emerged in recent years as a set of techniques and methodologies aiming at explaining machine learning (ML) models, and enabling humans to understand, trust, and manipulate the outcomes produced by artificial