Reasoning for CPS Education Using Surrogate Simulation Models

With developing an affordable, easily accessible and scalable online CPS laboratory to promote CPS education system, we are faced with and focused on a number of cyber-physical challenges including the model design and simulation strategies. The authors provide a complete process to simulate a behavior of a user-design CPS conveyor system. The user-design model is sent to the background, treated offline, and extracted the simulation result and finally feedback to user as an animation. The solution approach has two main parts, as the aspect of the modeling work, complex domain-specific conveyor design are defined in the Generic Modeling Environment (GME), it can be mapped and transformed to the global grid, another domain-specific model, which contains only one kind of node with huge dimension so that all different species of components in complex model are mapped to the typical nodes in grid, and it is easy to operate and simulate the nodes in global grid to fit for the need when multiple experiments being mapped to the grid. In this work, we only concerned the scenario of one experiment. The transformation and mapping process is implemented through Graph Rewriting and Transformation. As a background simulation, the Robocodes code is automatically generated by GME interpreter from global grid and is applied to generate the path logic to transmit the package, according to the package type in each input ports. After acquiring the transmit speed and path, Robocode simulation outputs the coordinate and time information to generate the Java animation. The final Java animation will be feedback to the user side to see the result of package transmission flow.

[1]  Anneke Kleppe,et al.  MDA explained - the Model Driven Architecture: practice and promise , 2003, Addison Wesley object technology series.

[2]  Ken Hartness Robocode: using games to teach artificial intelligence , 2004 .

[3]  Randy H. Katz,et al.  A view of cloud computing , 2010, CACM.

[4]  Hang Su,et al.  Model-Based Tool-Chain Infrastructure for Automated Analysis of Embedded Systems , 2006, ATVA.

[5]  A. Gokhale,et al.  CPS Laboratory-asa-Service : Enabling Technology for Readily Accessible and Scalable CPS Education , 2013 .

[6]  Michael Goshey,et al.  Radio Frequency Identification (RFID) , 2008, ACM SIGSPATIAL International Workshop on Advances in Geographic Information Systems.

[7]  Kyoungho An,et al.  Model-Driven Performance Analysis of Reconfigurable Conveyor Systems Used in Material Handling Applications , 2011, 2011 IEEE/ACM Second International Conference on Cyber-Physical Systems.

[8]  Li Yuan,et al.  MOOCs and open education: Implications for higher education , 2013 .

[9]  Gabor Karsai,et al.  An end-to-end domain-driven software development framework , 2003, OOPSLA '03.

[10]  Wayne H. Wolf,et al.  Cyber-physical Systems , 2009, Computer.

[11]  Gabor Karsai,et al.  Model-Integrated Computing , 1997, Computer.

[12]  Christian Floerkemeier,et al.  RFIDSim—A Physical and Logical Layer Simulation Engine for Passive RFID , 2008, IEEE Transactions on Automation Science and Engineering.

[13]  Gabor Karsai,et al.  The Generic Modeling Environment , 2001 .

[14]  Jacob Eisenstein,et al.  Evolving Robocode Tank Fighters , 2003 .

[15]  George Scalise,et al.  Leadership Under Challenge: Information Technology R&D in a Competitive World. An Assessment of the Federal Networking and Information Technology R&D Program , 2007 .

[16]  Luiz S. Martins-Filho,et al.  A Methodology for the Teaching of Dynamical Systems Using Analogous Electronic Circuits , 2006 .

[17]  Chen Zhang,et al.  Research on Human Sensory Architecture for Cyber Physical Systems , 2013, J. Networks.

[18]  Edward A. Lee Cyber Physical Systems: Design Challenges , 2008, 2008 11th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC).