Dr. Nicola Marchetti

Summary

The Internet of Things (IoT) is creating a new structure of awareness - a cybernetic one - upon physical processes. Industries of different kinds are expected to join soon this revolution, leading to the so-called Factories of the Future or Industry 4.0. Our considered IoT-based industrial cyber-physical system (CPS) works in three generic steps: 1) Large data acquisition / dissemination: A physical process is monitored by sensors that pre-process the (assumed large) collected data and send the processed information to an intelligent node (e.g. aggregator, central controller); 2) Big data fusion: The intelligent node uses machine learning techniques (e.g. data clustering, pattern recognition, neural networks) to convert the received ("big") data to useful information to guide short-term operational decisions related to the physical process; 3) Big data analytics: The physical process together with the acquisition and fusion steps can be virtualized, building then a cyber-physical process, whose dynamic performance can be analysed and optimized through visualization (if human intervention is available) or artificial intelligence (if the decisions are automatic) or a combination thereof.

Funding Agency

Irish Research Council

Programme

CHIST-ERA

Summary

The project aims finally to build a distributed network management framework for dense, distributed and heterogeneous IoT networks based on complex systems science paradigms. There are many communication technologies and testbeds but they do not talk the same language and solutions cannot be tested on multiple platforms, at the same time, in order to extract actionable knowledge the elements of a network and their interactions need to be modelled efficiently and complex systems science is very much a science which studies interactions between processes. The first part of the work deals with building a powerful and flexible taxonomy to describe how elements of an IoT network, interact with one another in a system-of-systems framework. Subsequently, a cross layer simulation frameworks will be designed to allow the study of interactions between all the network variables form PHY to application. A time-series causality analysis will be implemented to determine how a local action at a specific time can impact global behaviour in the future. Finally, the network behaviour is going to be studied with complex systems science to determine the most relevant processes in the network and develop distributed solutions once all the actionable variables are identified and the figures of merit are defined (by the data itself rather than by prior expert knowledge). The research builds upon the concrete work done in the biostatistics fields about structure learning (network inference), in complex systems science about inter-node interactions in time and space for causality, in practical network testing using real-life testbeds and IoT protocol design. The framework envisioned will be used to study and redefine how heterogeneous dense networks are designed and tested to allow seamless integrations of technologies and services.

Funding Agency

Marie Skłodowska-Curie & US Air Force Office of Scientific Research

Programme

COFUND

Summary

Massive MIMO in both, its co-located and distributed variant, has become an important part of future 5G plans so it needs to be understood well to be fully utilised. The nature and the scale of massive MIMO systems both imply existence of complexity observed in complex systems science manner, especially in the distributed massive MIMO case. Complexity in massive MIMO has not been investigated so far, therefore this research aims to fill this gap and grasp its complexity features by providing quantification, qualification and useful models of massive MIMO as a complex system. As a natural extension, this research also deals with devising control algorithms based on Massive MIMO models developed from complexity standpoint, verification of these algorithms and their implementation on real Massive MIMO systems, together with a thorough mathematical analysis using tools from control theory. Finally, this research will introduce reversible computing in Massive MIMO, investigating its effects on control and performance. Results of the research are diverse, ranging from publications explaining complexity in Massive MIMO setting, over novel tools and metrics developed for the specific application of complex systems science to Massive MIMO, to functional controller prototypes based on algorithms developed. This in turn represents the multidisciplinarity of the project as well, combining telecommunication systems with complex systems science, control theory, but also embedded system design and computer science. This project also includes some promising preliminary results of cellular automaton modelling and antenna selection control of Massive MIMO system.

Funding Agency

European Commission & Science Foundation Ireland

Programme

Marie Sklodowska-Curie COFUND

Summary

Recently machine-to-machine (M2M) communications (M2MCom) has emerged as an enabling technology for the practical realization of Internet-of-Things (IoT). Successful implementation of an M2MCom network demands high reliability, low latency, real-time operation and handling of huge amount of data, which, in turn, offers several challenges like connectivity among large number of machines with diverse functionalities, wide coverage area, resource and quality of service (QoS) constraints. In this research project, a cross-layer full-duplex (FD) design will be proposed to address the above-mentioned challenges of M2MCom systems. Adaptive FD MIMO (multiple-input-multiple-output) beamforming in the physical (PHY) layer will be combined with a request to send (RTS)/full-duplex clear to send (FCTS) mechanism based FD scheduling in the medium access (MAC) layer. The potentials of this design will be studied against two major applications of M2MCom, which are Smart Grids and Intelligent Transport System, and its performance will be evaluated through both numerical analysis and quantitative simulations. This project will also investigate the applicability of the proposed design for M2MCom in the millimetre-wave (mm-wave) frequency band using realistic mm-wave outdoor and indoor propagation models. Finally, the FD cross-layer PHY-MAC design will be validated practically through implementation on an IoT-based testbed.

Funding Agency

European Commission & Science Foundation Ireland

Programme

Marie Sklodowska-Curie COFUND

Summary

The "Internet of Things" (IoT) paves the way for the future world, where most daily objects are connected into Internet. Although it allows a multitude of new applications, facilitating daily lives and stimulating economy, it also poses security risks due to potential malicious attacks which can be executed remotely. Some of this risk comes from the use of a genuinely open wireless medium. Furthermore, since wireless IoT devices are often required to operate from small battery operated platforms, the use of computationally expensive cryptography algorithms is severely limited. The proposed research will develop a wireless communication system, where the transmitted information is readable only within certain physical area, while being perceived as noise elsewhere. This will be achieved by interdisciplinary research, combining reconfigurable antenna technology, multipath propagation channel modelling and MIMO-inspired signal processing. The system is expected to minimize computational complexity, facilitating secure communication between small nodes, as required for secure IoT applications. It aims to provide wireless SPIne, supporting security for all IoT products and devices. IoT is predicted to stimulate the global economy, introducing new products and even creating new markets with currently unconceivable applications. It is expected to open multiple business opportunities, while also transforming the community and facilitating daily lives. However these benefits will not survive without sufficient high-quality and affordable security, indispensable to build consumer's trust and confidence. The project addresses this issue by providing novel solutions to guarantee security, even when operating from small platforms.

Funding Agency

European Commission & Science Foundation Ireland

Programme

Marie Sklodowska-Curie COFUND