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Reconfiguration in Cyber-Physical Systems Sebastian Wtzoldt System Analysis and Modeling Group Prof. Holger Giese Motivation: Reconfiguration in Cyber-Physical Systems 2 Cyber-Physical Systems (CPS) are integrations of computation

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Reconfiguration in Cyber-Physical Systems

Sebastian Wätzoldt

System Analysis and Modeling Group

Prof. Holger Giese

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Motivation:

Reconfiguration in Cyber-Physical Systems

■ “Cyber-Physical Systems (CPS) are integrations of computation with physical processes.” [Lee2008] ■ “[CPS] … embed software, which: □ Record physical data via sensors □ Affect physical processes using actuators □ Actively interact with physical and digital world □ Are connected with one another and in global networks □ Use globally available data and services”

[acatech2011]

Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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[acatech2011]

Motivation:

Reconfiguration in Cyber-Physical Systems

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Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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[IEEESpectrumNov2012] http://spectrum.ieee.org/green-tech/advanced-cars/all-aboard-the-robotic-road-train

Motivation:

Reconfiguration in Cyber-Physical Systems

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[IEEESpectrumNov2012] http://spectrum.ieee.org/green-tech/advanced-cars/all-aboard-the-robotic-road-train

Motivation:

Reconfiguration in Cyber-Physical Systems

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Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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[IEEESpectrumNov2012] http://spectrum.ieee.org/green-tech/advanced-cars/all-aboard-the-robotic-road-train

Motivation:

Reconfiguration in Cyber-Physical Systems

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Software adaptation is (1) the adaptation of a software system or (2) the processes and activities related to the adaptation of a software system.

Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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■ Parameter adaptation vs. compositional adaptation □ “Parameter adaptation modifies program variables that determine behavior.” [McKinley2004] □ “[…] compositional adaptation exchanges algorithmic or structural system components with others that improve a program’s fit to its current environment.” [McKinley2004] ■ Static adaptation vs. dynamic adaptation [McKinley2004] ■ Internal adaptation vs. external adaptation [Salehie2009]

[Schäfer2007] [Musliner1999]

Motivation:

Reconfiguration in Cyber-Physical Systems

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Points to Discuss

■ (I) cover dynamic behavior via explicit modeled and coexisting feedback loops ■ (II) reduce complexity and enable interaction via abstraction using runtime models following the model driven engineering approach ■ (III) consider specific domains and nonfunctional properties ■ (IV) support concurrent and distributed interactions of subsystems

Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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Reconfiguration in Cyber-Physical Systems (Adaptation)

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Points to Discuss: Cyber-Physical Systems Laboratory

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Feedback Loop

Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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Adaptable Cyber-Physical System

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Adaptation Engine

Feedback Loop

Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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Adaptable Cyber-Physical System Monitor Analyze Plan Execute Knowledge

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Adaptation Engine

Feedback Loop with Runtime Models

■ External adaptation approach as proposed in [Salehie2009] ■ Feedback loop with four activities: □ Monitor-Analyse-Plan- Execute  Knowledge (MAPE-K) [IBMKephart2003] ■ Runtime models as on-line representation of the running system [Vogel2011] □ Reflection models □ Evaluation models □ Change models □ Execution models

Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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Adaptable Cyber-Physical System Monitor Analyze Plan Execute Knowledge

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Multiple Feedback Loops

Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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Adaptable Cyber-Physical System Self- healing

M A P E

Self-

ptimizing

M A P E

Separation of loops: ■ Different concerns [Frey2012] □ Self-healing □ Self-optimizing □ Hard real-time adaptation

vs. soft real-time

adaptation ■ Local vs. global adaptation

[Gueye2012]

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Multiple Feedback Loops

Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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Adaptable Cyber-Physical System

M A P E M A P E

Problems: ■ Inter-loop communication ■ Model exchange ■ Concurrency coordination ■ Contradicting model manipulation Separation of loops: ■ Different concerns [Frey2012] □ Self-healing □ Self-optimizing □ Hard real-time adaptation

vs. soft real-time

adaptation ■ Local vs. global adaptation

[Gueye2012]

Self- healing Self-

ptimizing

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Multiple Layered Feedback Loops

■ Handle different problems on different level of abstraction e.g. inspired by adaptive control theory

[Kokar1999]

■ Hierarchical control architectures

[IBMKephart2003]

■ Proposed reference architecture for self-managed software systems

[Kramer2007]

Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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Adaptable Cyber-Physical System Hard Real-Time Adaptation

M A P E

Self- healing

M A P E

Self-

ptimizing

M A P E …

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Distributed Multiple Layered Feedback Loops

■ Complex CPS with several independent, heterogeneous subsystems □ Autonomous robots in a warehouse □ Distributed traffic management ■ Runtime models □ Basic communication concept □ Exchange of information possible □ Learn, adapt on new situations via model driven techniques

Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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Adaptable CPS HRT Self-

ptimizing

M A P E …

Adaptable CPS

…

Self- H. HRT

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Example: Cyber-Physical Systems Laboratory

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Example

Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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Adaptable Cyber-Physical System

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Example: Failure Detection and Repair

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Adaptable Cyber-Physical System Failure Detection + Repair

M A P E

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Example: Failure Detection and Repair  Monitor

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Failure Detection + Repair

M A P E

Monitor Knowledge Adaptable Cyber-Physical System

<<Component>> Navigation Logic <<Sensor>> Obstacle Detection <<Sensor>> Localization <<Actuator>> Wheel

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<<Component>> Navigation Logic <<Sensor>> Obstacle Detection <<Sensor>> Localization <<Actuator>> Wheel

Example: Failure Detection and Repair  Monitor

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M A P E

Monitor Knowledge Adaptable Cyber-Physical System Failure Detection + Repair

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Example: Failure Detection and Repair  Analyze

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M A P E

Knowledge Rules Analyze Adaptable Cyber-Physical System

<<Component>> Navigation Logic <<Sensor>> Obstacle Detection <<Sensor>> Localization <<Actuator>> Wheel

Failure Detection + Repair

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Example: Failure Detection and Repair  Analyze

Sebastian Wätzoldt | Reconfiguration in Cyber-Physical Systems | HPI Symposium @ SAP

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M A P E

Knowledge Analyze Rules Adaptable Cyber-Physical System

<<Component>> Navigation Logic <<Sensor>> Obstacle Detection <<Sensor>> Localization <<Actuator>> Wheel

replace Failure Detection + Repair

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Example: Failure Detection and Repair  Plan

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M A P E

Knowledge Plan Adaptable Cyber-Physical System

<<Component>> Navigation Logic <<Sensor>> Obstacle Detection <<Sensor>> Localization <<Actuator>> Wheel

replace Failure Detection + Repair

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Example: Failure Detection and Repair  Plan

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M A P E

Knowledge Plan Component repository

1) Remove old component 2) Load backup component 3) Connect backup component

Adaptable Cyber-Physical System

<<Component>> Navigation Logic <<Sensor>> Obstacle Detection <<Sensor>> Localization <<Actuator>> Wheel

replace

<<Sensor>> BACKUP Obstacle Detection

Failure Detection + Repair

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Example: Failure Detection and Repair  Execute

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M A P E

Knowledge Execute Adaptable Cyber-Physical System

1) Remove old component 2) Load backup component 3) Connect backup component <<Component>> Navigation Logic <<Sensor>> Obstacle Detection <<Sensor>> Localization <<Actuator>> Wheel

replace

<<Sensor>> BACKUP Obstacle Detection

Failure Detection + Repair

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Summary: Cyber-Physical Systems Laboratory

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Summary:

Reconfiguration in Cyber-Physical Systems

[acatech2011]

Adapt cyber-physical systems at runtime: A research challenge!

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References

■ Erik Coelingh, Stefan Solyom. All Aboard the Robotic Road Train. IEEE Spectrum, November,2012. http://spectrum.ieee.org/green-tech/advanced-cars/all-aboard-the-robotic-road-train ■ Hyun Jung La, Soo Dong Kim. A Service-Based Approach to Designing Cyber Physical

Systems. Computer and Information Science, ACIS International Conference on, pp. 895-900,

2010 IEEE/ACIS 9th International Conference on Computer and Information Science, 2010 ■ Edward A. Lee. Cyber Physical Systems: Design Challenges. Technical report, EECS Department, University of California, Berkeley, UCB/EECS-2008-8, Jan, 2008. ■ Wilhelm Schäfer and Heike Wehrheim. 2007. The Challenges of Building Advanced Mechatronic Systems. In 2007 Future of Software Engineering (FOSE '07). IEEE Computer Society, Washington, DC, USA, 72-84. DOI=10.1109/FOSE.2007.28 http://dx.doi.org/10.1109/FOSE.2007.28 ■ David J. Musliner, Robert P. Goldman, Michael J. Pelican and Kurt D. Krebsbach. Self-Adaptive Software for Hard Real-Time Environments. In IEEE Intelligent Systems, Vol. 14(4), July 1999. ■ Philip McKinley, Seyed Masoud Sadjadi, Eric P. Kasten and Betty H. Cheng. Composing Adaptive

Software. In IEEE Computer, Vol. 37(7):56-64, July 2004.

■ Mazeiar Salehie and Ladan Tahvildari. Self-adaptive software: Landscape and research

challenges. In ACM Trans. Auton. Adapt. Syst., Vol. 4(2):1--42, ACM, New York, USA , 2009.

■ Thomas Vogel, Andreas Seibel and Holger Giese. The Role of Models and Megamodels at

Runtime. In Models in Software Engineering, Workshops and Symposia at MODELS 2010, Oslo,

Norway, October 3-8, 2010, Reports and Revised Selected Papers, Vol. 6627:224-238 of Lecture Notes in Computer Science (LNCS), Springer-Verlag, May 2011.

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References

■ Jeffrey O. Kephart and David Chess. The Vision of Autonomic Computing. In Computer, Vol. 36(1):41--50, IEEE Computer Society Press, Los Alamitos, CA, USA, January 2003. ■ Sylvain Frey, Ada Diaconescu and Isabelle M. Demeure. Architectural Integration Patterns for Autonomic Management Systems. In Proceedings of the 9th IEEE International Conference and Workshops on the Engineering of Autonomic and Autonomous Systems (EASe 2012), 2012. ■ Soguy Mak Karé Gueye, Noel De Palma and Eric Rutten. Coordinating Energy-aware Administration Loops Using Discrete Control. In Proceedings of the 8th International Conference on Autonomic and Autonomous Systems (ICAS 2012), Pages 99--106, IARIA, 2012. ■ Mieczyslaw M. Kokar, Kenneth Baclawski and Yönet A. Eracar. Control Theory-Based Foundations of Self-Controlling Software. In Intelligent Systems and their Applications, Vol. 14(3):37-45, 1999. ■ Jeff Kramer and Jeff Magee. Self-Managed Systems: an Architectural Challenge. In FOSE '07: 2007 Future of Software Engineering, Pages 259--268, IEEE Computer Society, Washington, DC, USA , 2007. ■ acatech, ed. (2011). Cyber-Physical Systems: Driving Force for Innovation in Mobility, Health, Energy and Production (acatech POSITION PAPER). acatech -- National Academy of Science and Engineering , Munich, Germany, 2011. ■ Geisberger, E. and Broy, M. agendaCPS: Integrierte Forschungsagenda Cyber-Physical

Systems. acatech STUDIE, Springer, 2012.