A concept lattice-based event model for Cyber-Physical Systems

Cyber-Physical Systems (CPS) involve communication, computation, sensing, and actuating through heterogeneous and widely distributed physical devices and computational components. The close interactions of these systems with the physical world places events as the major building blocks for the realization of CPS. More specifically, the system components and design principles should be revisited with a strictly event-based approach. In this paper, a concept lattice-based event model for CPS is introduced. Under this model, a CPS event is uniformly represented by three components: event type, its internal attributes, and its external attributes. The internal and external attributes together characterize the type, spatiotemporal properties of the event as well as the components that observe it. A set of event composition rules are defined where the CPS event composition is based on a CPS concept lattice. The resulting event model can be used both as an offline analysis tool as well as a run-time implementation model due to its distributed nature. A real-life smart home example is used to illustrate the proposed event model. To this end, a CPS event simulator is implemented to evaluate the developed event model and compare with the existing Java implementation of the smart home application. The comparison result shows that the event model provides several advantages in terms of flexibility, QoS support, and complexity. The proposed event model lay the foundations of event-based system design in CPS.

[1]  Natalya Keberle,et al.  An Ontology of Environments, Events, and Happenings , 2008, 2008 32nd Annual IEEE International Computer Software and Applications Conference.

[2]  Rudolf Wille,et al.  Formal Concept Analysis as Mathematical Theory of Concepts and Concept Hierarchies , 2005, Formal Concept Analysis.

[3]  Leslie Lamport,et al.  Time, clocks, and the ordering of events in a distributed system , 1978, CACM.

[4]  Hari Balakrishnan,et al.  6th ACM/IEEE International Conference on on Mobile Computing and Networking (ACM MOBICOM ’00) The Cricket Location-Support System , 2022 .

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

[6]  Carolyn L. Talcott,et al.  Cyber-Physical Systems and Events , 2008, Software-Intensive Systems and New Computing Paradigms.

[7]  Narain H. Gehani,et al.  Composite Event Specification in Active Databases: Model & Implementation , 1992, VLDB.

[8]  Gerd Stumme,et al.  CEM-Visualisation and Discovery in Email , 2000, PKDD.

[9]  Klaus R. Dittrich,et al.  Detecting composite events in active database systems using Petri nets , 1994, Proceedings of IEEE International Workshop on Research Issues in Data Engineering: Active Databases Systems.

[10]  Ophir Frieder,et al.  Interval-Based Timing Constraints Their Satisfactions and Applications , 2008, IEEE Transactions on Computers.

[11]  Max J. Egenhofer,et al.  Reasoning about Gradual Changes of Topological Relationships , 1992, Spatio-Temporal Reasoning.

[12]  Peter W. Eklund,et al.  Algorithms for Creating Relational Power Context Families from Conceptual Graphs , 1999, ICCS.

[13]  Gregor Snelting,et al.  Reengineering of configurations based on mathematical concept analysis , 1996, TSEM.

[14]  Jean Sallantin,et al.  Structural Machine Learning with Galois Lattice and Graphs , 1998, ICML.

[15]  Christian Lindig Concept-Based Component Retrieval , 1995 .

[16]  Insup Lee,et al.  Semantics of High-Level Event Definition , 2007 .

[17]  Koushik Sen,et al.  Rule-Based Runtime Verification , 2004, VMCAI.

[18]  Umeshwar Dayal,et al.  The architecture of an active database management system , 1989, SIGMOD '89.

[19]  Rudolf Wille,et al.  Restructuring Lattice Theory: An Approach Based on Hierarchies of Concepts , 2009, ICFCA.

[20]  Chen Xia,et al.  Comparison of three Kalman filters for an indoor passive tracking system , 2007, 2007 IEEE International Conference on Electro/Information Technology.

[21]  Mahesh Viswanathan,et al.  Java-MaC: A Run-Time Assurance Approach for Java Programs , 2004, Formal Methods Syst. Des..

[22]  Gerd Stumme,et al.  CEM - A program for visualisation and discovery in email , 2000, KDD 2000.

[23]  Sharma Chakravarthy Sentinel: an object-oriented DBMS with event-based rules , 1997, SIGMOD '97.

[24]  Frank Tip,et al.  Reengineering class hierarchies using concept analysis , 1998, SIGSOFT '98/FSE-6.

[25]  John F. Roddick,et al.  Survey of Spatio-Temporal Databases , 1999, GeoInformatica.

[26]  Ying Tan,et al.  Spatio-Temporal Event Model for Cyber-Physical Systems , 2009, 2009 29th IEEE International Conference on Distributed Computing Systems Workshops.

[27]  Chan-Gun Lee,et al.  Specifying timing constraints and composite events: an application in the design of electronic brokerages , 2004, IEEE Transactions on Software Engineering.

[28]  Erik T. Mueller Automating commonsense reasoning using the event calculus , 2009, CACM.

[29]  Peter W. Eklund,et al.  Scalability in Formal Concept Analysis , 1999, Comput. Intell..

[30]  Hanêne Ben-Abdallah,et al.  Formally specified monitoring of temporal properties , 1999, Proceedings of 11th Euromicro Conference on Real-Time Systems. Euromicro RTS'99.

[31]  David E. Culler,et al.  The nesC language: A holistic approach to networked embedded systems , 2003, PLDI.

[32]  David E. Culler,et al.  TOSSIM: accurate and scalable simulation of entire TinyOS applications , 2003, SenSys '03.

[33]  Marek J. Sergot,et al.  A logic-based calculus of events , 1989, New Generation Computing.

[34]  Chan-Gun Lee,et al.  The monitoring of timing constraints on time intervals , 2002, 23rd IEEE Real-Time Systems Symposium, 2002. RTSS 2002..

[35]  Sharma Chakravarthy,et al.  SnoopIB: Interval-based event specification and detection for active databases , 2003, Data Knowl. Eng..