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CINI consortium, Departement of Computer Science and System Engineering (DIS) of University of Naples FEDERICO II, Università degli Studi di FIRENZE (UniFI), Università degli Studi di MODENA e REGGIO EMILIA (UniMORE), Università degli Studi di NAPOLI "Parthenope" (UniPARTHENOPE), Università degli Studi di ROMA "La Sapienza" (UniRM)


The overall objective throughout the whole project will be the advancement of knowledge in the field of resiliency assurance and improvement in complex systems, in particular in the context of LCCIs, which are characterized by challenging aspects only in part addressed in the past. In particular, the project will foster the advancement of the state of art in the fields of distributed systems (e.g., novel gossip communication schemes, more efficient and reliable data dissemination techniques), hardware and software diagnosis (e.g., application of most recent advancements in machine learning for handling uncertainty in LCCIs), and software engineering (e.g., more reliable and cost/time efficient techniques for evaluation of component-based systems, by means of novel testing and modeling approaches). Those advancements are crucial for improving trustworthiness on ICT facilities, and spreading their adoption in very critical scenarios involving crucial infrastructures for modern society (e.g., water and energy supply, transports, healthcare), in order to make a step towards a future world in which ICT will seamlessly supervise physical systems, with minimal human supervision, and automatic maintenance, update and evolution of the system.

The project will deliver novel contributions to the problem of assessing and assuring resiliency, in terms of:

  1. Modeling techniques, to be used by designers to improve their designs, and system operators to evaluate at runtime resiliency attributes (e.g., the expected time and location of a failure).
  2. Algorithms, strategies and architectures to enable reliable communication, and automatic on-line diagnosis and reconfiguration.
  3. Experimental evaluation and prototypal implementations of the proposed techniques, in order to demonstrate their effectiveness for LCCIs.



MobiLab Group:
Roberto Natella
Antonio Pecchia
Domenico Di Leo
Flavio Frattini
Anna Lanzaro
Francesco Fucci
Fabio Scippacercola
Raffaele Della Corte


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