T-REX Operating Unit 3

OU3 is one of the six Operating Units of the Progetto Premiale T-REX. It is focused on the development of adaptive optics instrumentation for the European Extremely Large Telescope. The main activities of OU3 are the MAORY adaptive optics module, the MICADO infrared camera, the characterisation and forecast of atmospheric parameters for the E-ELT site and general developments for future adaptive optics systems. <P /

Gambling on fairness: A fair scheduler for IIoT communications based on the shell game

The Industrial Internet of Things (IIoT) paradigm represents nowadays the cornerstone of the industrial automation since it has introduced new features and services for different environments and has granted the connection of industrial machine sensors and actuators both to local processing and to the Internet. One of the most advanced network protocol stack for IoT-IIoT networks that have been developed is 6LoWPAN which supports IPv6 on top of Low-power Wireless Personal Area Networks (LoWPANs). 6LoWPAN is usually coupled with the IEEE 802.15.4 low-bitrate and low-energy MAC protocol that relies on the time-slotted channel hopping (TSCH) technique. In TSCH networks, a coordinator node synchronizes all end-devices and specifies whether (and when) they can transmit or not in order to improve their energy efficiency. In this scenario, the scheduling strategy adopted by the coordinator plays a crucial role that impacts dramatically on the network performance. In this paper, we present a novel scheduling strategy for time-slot allocation in IIoT communications which aims at the improvement of the overall network fairness. The proposed strategy mimics the well-known shell game turning the totally unfair mechanics of this game into a fair scheduling strategy. We compare our proposal with three allocation strategies, and we evaluate the fairness of each scheduler showing that our allocator outperforms the others

A Novel IoT-Based Architecture for Self-Adaptive Aerodynamic Flow Control System for Motorcycle

In this paper, we introduce an autonomous system for aerodynamic flow control for motorcycle based on the Internet of Things (IoT) paradigm. The architecture we propose adapts dynamically the flows at the traveling conditions, in order to obtain an improvement of performance and vehicle stability. In our architecture, we deploy a group of sensors on the top surface of the wings to sense the air pressure. We design a centralized on-board unit that computes a new wing angle of attack according to the data received from the sensors. The on-board unit includes a local information database which represents its knowledge: it stores both the data gathered by the sensors and the fluid dynamics model used to compute and adjust the angle of attack. The on-board database is periodically updated transmitting all the measurements gathered from the sensors to a High-Performance Cloud Data Center (DC) which executes a parallel version of Computational Fluid Dynamics (CDF) algorithms, computes the updated model, and transmits the processed information back to the on-board unit. We perform preliminary tests in the wind tunnel, and we show how the cooperation between IoT devices and DC can reduce the on-board unit computational effort

From Sensors to the Cloud: A Real-Time Use-case on Vertical Integration

We present a vertical integration of a real-time Industrial Internet of Things environment with Cloud computing functionalities. We designed our testbed to implement self-adaptive wings for motorbikes using pressure values sensed in specific locations of the motorbike as input data collected exploiting open-hardware devices called OpenMotes which communicate through a low-power, delay-constrained wireless network based on the 6LoWPAN protocol stack. Our real-time on-board unit elaborates the data, and it computes the new angle of attack of two wings. The total response time of the system is in the order of 100 ms and meets the real-time requirements that constrains our scenario. Finally, we integrate our system with Cloud functionalities that we use for storing the acquired data on a time-series database

Open CLORO: An open testbed for cloud robotics

The introduction of the Cloud paradigm has rapidly changed IT-infrastructures in modern organizations. The application of Cloud systems to manage a growing number of IoT devices such as sensors is continually unfolding and revealing new opportunities. A notable field of research is related to the development of models, applications and real testbed on robots that can be managed and coordinated remotely at a higher layer involving network communications. In this paper, we present Open CLORO: an open testbed for Cloud robotics. We propose Open CLORO, which serves as a benchmark for real experiments for various network applications in which the Robots are equipped with programmable devices that also provide network connectivity and grant access from remote. We provide a detailed overview of the proposed architecture that can be effective for developing and testing not only robots-related experiments but also a wide number of network applications such as distributed coordination, vehicle-to-vehicle communications, and Cloud-based management services