Cross-layer model-based framework for multi-objective design of Reconfigurable systems in uncertain hybrid environments

SmartCPS-concertation Event Brussels, 30 th Jan. 2017 Cross-layer model-based framework for multi-objective design of Reconfigurable systems in uncertain hybrid environments

SRC: Sensors 2015, 15(4), 7172-7205; doi:10.3390/s150407172 CYBER PHYSICAL SYSTEMS Cyber and Physical layers interact and influence each other by means of sensors and actuators. 6.4 billion connected in 2016 will become 20.8 billion by 2020.

security cost dependable Safety Security Certif. Distrib. HMI Seamless MPSoC Energy CYBER PHYSICAL SYSTEMS Complex Functionalities IDC - Design of Future ES (SMART 2009/0063) Colliding Constraints Automotive x x x x x x x Aerospace x x x x x x x Healthcare x x x x x x x x Consumer x x x CONTINUOUS OPERATION COMPUTATION real time ICT NON-FUNCTIONAL DYNAMIC performance energy-aware INTERCONNECTED COMMUNICATION EMBEDDED FUNCTIONAL portable PHYSICAL ADAPTIVITY

CERBERO Cross-layer model-based framework for multi-objective design of Reconfigurable systems in uncertain hybrid environments Cross-Layer: Computational, physical and communication layer sare going to be crossoptimized, taking into consideration that they are intrinsically concurrent, among each other and internally. Model-Based: Address the current lack of a comprehensive modelling strategy for heterogeneous CPS supporting model-to-model (e.g. from computational to communication view) mapping and synchronization (e.g. from time-continuum and event-driven) interfaces with feedback loops. Multi-Objective: Continuous guarantees and analysis of functional and nonfunctional requirements by means of a library of reusable Key Performance Indicators (KPIs). Uncertain Hybrid Environments: Optimization of dynamic physical-human systems characterized by uncertain parameters. Reconfigurable: Address the current lack in adaptivity modelling and support. CPS should autonomously adapt to rapid changes in the environment and in the system itself.

CONSORTIUM LE SME RTO U IL IT ES NL UK FR CH Use Case: TASE (space), AS (ocean) and TNO (smart travelling) with support of: S&T (space and smart travelling), AI and CRF (smart travelling). Framework: IBM (framework architect) and AI (framework developer). R&D Components and Technology: IBM, AI, TNO, AS, UniSS, INSA, UniCA, UPM and USI

Overview & Implementation CERBERO Pillars Model-centric approach to scenario and system definition, including the properties to be addressed. Multi-layer adaptation enabling runtime reaction to external stimulus and possible to the variation/evolution of the scenario or constraints. Continuous design and operational framework for highly interconnected systems WP WP3 WP4 WP5

CERBERO Integrated Framework - KoM

Use Cases Self-Healing System for Planetary Exploration (TASE): The objective of this use case is twofold. On one side it focusses on a single unique embedded CPS; while, on the other, it focusses on its integration with other systems of a planetary exploration mission. CERBERO is mainly conceived to define self-healing and self-adaptive processing systems capable of operating in such a critical environment. Ocean Monitoring (AmbieSense): Smart video-sensing unmanned vehicles with immersive environmental monitoring capabilities and capable of self-operation and navigation. CERBERO will define algorithms for data analysis and information fusion to enable smart adaptation strategies to address rapidly changing environment conditions in order to obtain or maintain positions on sea. Smart Travelling for Electric Vehicle (TNO-CRF-Abinsula): Highly networked scenario composed of heterogeneous concurrent subsystems including the Electric Vehicle, the Person possessing a Personal Agenda, the Smart Energy Grid and the Smart Mobility that provides mobility-aware functionality (e.g. parking places, charge points, etc.). Provide a high degree of autonomy and support for adaptability plus modelling and managing the distributed communication layers are the CERBERO challenges.

Contacts and Info www.cerbero-h2020.eu info@cerbero-h2020.eu @CERBERO_h2020 Coordinator: Michal Masin (IBM), michaelm@il.ibm.com Scientific Coordinator: Francesca Palumbo (UniSS), fpalumbo@uniss.it Innovation Manager: Katiuscia Zedda (Abinsula), katiuscia.zedda@abinsula.com Dissemination-Communication Manager: Francesco Regazzoni (USI), francesco.regazzoni@usi.ch