CERBERO: Cross-layer modEl-based fRamework for multi-oBjective dEsign of reconfigurable systems in unceRtain hybRid envirOnments: Invited paper: CERBERO teams from UniSS, UniCA, IBM Research, TASE, INSA-Rennes, UPM, USI, Abinsula, AmbieSense, TNO, S&T, CRF

Cyber-Physical Systems (CPS) are embedded computational collaborating devices, capable of sensing and controlling physical elements and, often, responding to humans. Designing and managing systems able to respond to different, concurrent requirements during operation is not straightforward, and introduce the need of proper support at design-time and run-time. The Cross-layer modEl-based fRamework for multi-oBjective dEsign of Reconfigurable systems in unceRtain hybRid envirOnments (CERBERO) EU project has developed a design environment for adaptive CPS. CERBERO approach leverages on model-based methodologies including different technologies and tools developed to cover design and operation from user interactions down to low level computing layer implementation.

[1]  Luigi Raffo,et al.  Challenging CPS Trade-off Adaptivity with Coarse-Grained Reconfiguration , 2017, ApplePies.

[2]  Yair Wand,et al.  Emancipating instances from the tyranny of classes in information modeling , 2000, TODS.

[3]  Maxime Pelcat,et al.  Spider: A Synchronous Parameterized and Interfaced Dataflow-based RTOS for multicore DSPS , 2014, 2014 6th European Embedded Design in Education and Research Conference (EDERC).

[4]  Luigi Raffo,et al.  Cross-layer design of reconfigurable cyber-physical systems , 2017, Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017.

[5]  Eduardo Juárez Martínez,et al.  Automatic instrumentation of dataflow applications using PAPI , 2018, CF.

[6]  Eduardo de la Torre,et al.  IMPRESS: Automated Tool for the Implementation of Highly Flexible Partial Reconfigurable Systems with Xilinx Vivado , 2018, 2018 International Conference on ReConFigurable Computing and FPGAs (ReConFig).

[7]  Luca Pulina,et al.  Consistency of Property Specification Patterns with Boolean and Constrained Numerical Signals , 2018, NFM.

[8]  Luigi Raffo,et al.  Multi-Grain Reconfiguration for Advanced Adaptivity in Cyber-Physical Systems , 2018, 2018 International Conference on ReConFigurable Computing and FPGAs (ReConFig).

[9]  Reiner W. Hartenstein,et al.  Coarse grain reconfigurable architecture (embedded tutorial) , 2001, ASP-DAC '01.

[10]  Simon A. Dobson.  Component-Oriented Approaches to Context-Aware Computing , 2004, ECOOP Workshops.

[11]  Ofer M. Shir,et al.  Algorithms for Finding Maximum Diversity of Design Variables in Multi-Objective Optimization , 2012, CSER.

[12]  Eduardo de la Torre,et al.  FPGA-Based High-Performance Embedded Systems for Adaptive Edge Computing in Cyber-Physical Systems: The ARTICo3 Framework , 2018, Sensors.

[13]  Rodolfo E. Haber,et al.  Self-adaptive systems: A survey of current approaches, research challenges and applications , 2013, Expert Syst. Appl..

[14]  Paolo Meloni,et al.  Reconfigurable coprocessors synthesis in the MPEG-RVC domain , 2015, 2015 International Conference on ReConFigurable Computing and FPGAs (ReConFig).

[15]  Ayse Göker,et al.  Searching of Self-similar Spaces , 2018 .

[16]  Maxime Pelcat,et al.  Preesm: A dataflow-based rapid prototyping framework for simplifying multicore DSP programming , 2014, 2014 6th European Embedded Design in Education and Research Conference (EDERC).

[17]  Eduardo de la Torre,et al.  Power management techniques in an FPGA-based WSN node for high performance applications , 2012, 7th International Workshop on Reconfigurable and Communication-Centric Systems-on-Chip (ReCoSoC).

[18]  Paolo Meloni,et al.  Power-Awarness in Coarse-Grained Reconfigurable Multi-Functional Architectures: a Dataflow Based Strategy , 2017, J. Signal Process. Syst..

[19]  Julio A. de Oliveira Filho,et al.  Model-Based Architecture Optimization for Self-Adaptive Networked Signal Processing Systems , 2014, 2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems.

[20]  Tibor Bosse,et al.  Developing ePartners for human-robot teams in space based on ontologies and formal abstraction hierarchies , 2017, Int. J. Agent Oriented Softw. Eng..