Description

With ever-growing proliferation of cyber-physical systems in all walks of life, their properties like dependability, security and timeliness are of utmost importance. The built-in intelligence in cyber-physical systems will have to face these challenges to ensure problem-free, continuous operation of such systems as the users expect 7x24 availability, maximum security and real time operability.
The emergence of non-trivial embedded sensor units and cyber-physical systems has made possible the design and implementation of such sophisticated applications where large amounts of real-time data are collected, possibly to constitute a big data picture as time passes. Within this framework, intelligence mechanisms play a key role to provide systems with advanced functionalities. Intelligent mechanisms are, in fact, needed to guarantee appropriate performances within an evolving, time invariant environment, optimally harvest and manage the residual energy, identify faults within a model-free framework, solve the compromise between output accuracy and computational complexity.

• Dependability and reliability, concepts and measures
• Dependability modeling and tools
• Fault detection, diagnosis and recovery
• Fault tolerance and autonomic computing
• Adaptation and learning in embedded applications (voltage-frequency scaling, adaptive sampling, energy harvesting)
• Designing static vs. dynamic applications (detect& react mechanism, Learning in evolving environments, code-level adaptation)
• Model free fault diagnosis for cyber-physical systems

References

• C.Alippi, Intelligence for Embedded Systems: a Methodological approach, Springer, 2014

• E.Dubrova, Fault-Tolerant Design, Springer, 2013

• Technical papers and reference material provided by the professors