Ricerc@Sapienza

Efficient application of carbon nanotubes (CNTs) in nano-devices and nano-materials requires comprehensive understanding of their mechanical properties. As observations suggest size dependent behaviour, non-classical theories preserving the memory of body’s internal structure via additional material parameters offer great potential when a continuum modelling is to be preferred.

We consider the problem of managing a 5G network composed of virtualized entities, called Reusable Functional Blocks (RFBs), as proposed by the Horizon 2020 SUPERFLUIDITY project. The RFBs are used to decompose network functions and services, and are deployed on top of physical nodes, in order to realize the 5G functionalities. After formally modelling the RFBs in a 5G network, as well as the physical nodes hosting them, we formulate the problem of managing the 5G network through the RFBs, in order to satisfy different Key Performance Indicators (KPIs) to users.

We consider a class of optimal control problems for measure-valued nonlinear transport equations describing traffic flow problems on networks. The objective is to minimise/maximise macroscopic quantities, such as traffic volume or average speed, controlling few agents, e.g. smart traffic lights and automated cars. The measure theoretic approach allows to study in a same setting local and non-local drivers interactions and to consider the control variables as additional measures interacting with the drivers distribution.

Pipelining a combinational logic data-path without introducing pipeline stage delay imbalance is a key requirement for efficient digital processing. Balanced pipelining is easily achieved by simple logical effort optimisation when the interconnect and fan-out delay overhead is small and homogeneously distributed. When the target microarchitecture design includes isolated long interconnects, such as buses, optimal pipeline stage balancing becomes a tricky problem.

This paper describes the state of advancement achieved in the OptiYard research project in the use of optimisation algorithms in interaction with microsimulation of the rail-yard and surrounding network towards realtime yard management and communication with the network. Two case studies, a hump marshalling yard (mainly Single Wagon Load traffic) and a flat shunting yard (mainly intermodal traffic), were represented with state-of-the art microsimulation models, combined with innovative optimisation algorithms. Some specialistic information on the nature of the models is provided.