Mathematical models towards self-organizing formal federation languages based on conceptual models of information exchange capabilities

Conceptual models capture information that is crucial for composability of legacy solutions that is not formally captured in the derived technical artifacts. It is necessary to make this information available for the selection (or elimination) of available solutions, their orchestration, and their execution. Current standards barely address this class of problems. The approach presented in this paper is the first step towards self-organizing federation languages. The system interfaces are described in form of exchangeable data. The context of information exchange (syntax, semantics, and pragmatics) is captured as metadata. These metadata are used to identify the elements of a formal federation language that links model composability and simulation interoperability based on conceptual model elements. The paper describes the formal process of selection, orchestration, and execution and the underlying mathematics for the information exchange specifications that bridge conceptual and engineering levels of the federation process.

[1]  John McCarthy,et al.  SOME PHILOSOPHICAL PROBLEMS FROM THE STANDPOINT OF ARTI CIAL INTELLIGENCE , 1987 .

[2]  Heiner Stuckenschmidt,et al.  Ontology-Based Integration of Information - A Survey of Existing Approaches , 2001, OIS@IJCAI.

[3]  Peter Staub,et al.  Semantic Interoperability through the Definition of Conceptual Model Transformations , 2008, Trans. GIS.

[4]  E. F. CODD,et al.  A relational model of data for large shared data banks , 1970, CACM.

[5]  Paul K. Davis,et al.  Observations on new developments in composability and multi-resolution modeling , 2007, 2007 Winter Simulation Conference.

[6]  Ronald J. Brachman,et al.  What IS-A Is and Isn't: An Analysis of Taxonomic Links in Semantic Networks , 1983, Computer.

[7]  F. E..  A Relational Model of Data Large Shared Data Banks , 2000 .

[8]  Jean-François Mascari,et al.  Complex adaptive services , 2007, Int. J. Bus. Process. Integr. Manag..

[9]  Stefano Redaelli,et al.  Models, Abstractions and Phases in Multi-Agent Based Simulation , 2006, WOA.

[10]  Paul F. Reynolds,et al.  Consistency maintenance in multiresolution simulation , 1997, TOMC.

[11]  Ronald J. Brachman,et al.  ON THE EPISTEMOLOGICAL STATUS OF SEMANTIC NETWORKS , 1979 .

[12]  Galia Angelova,et al.  From Conceptual Structures to Semantic Interoperability of Content , 2007, ICCS.

[13]  Ernest H. Page,et al.  Toward a Family of Maturity Models for the Simulation Interconnection Problem , 2004 .

[14]  Bernard P. Zeigler,et al.  Modeling & Simulation-Based Data Engineering: Introducing Pragmatics into Ontologies for Net-Centric Information Exchange , 2007 .

[15]  Stewart Robinson,et al.  Conceptual modelling for simulation Part I: definition and requirements , 2008, J. Oper. Res. Soc..

[16]  Andres Sousa-Poza,et al.  System of systems engineering , 2003, IEEE Engineering Management Review.

[17]  Andreas Tolk,et al.  Model-Based Data Engineering for Web Services , 2005, IEEE Internet Comput..

[18]  Tuncer Ören,et al.  An ontology-based dictionary of understanding as a basis for software agents with understanding abilities , 2007, SpringSim '07.

[19]  Alvin S. Lim,et al.  Requirements and design principles for multisimulation with multiresolution, multistage multimodels , 2007, 2007 Winter Simulation Conference.

[20]  Andreas Tolk,et al.  What Comes After the Semantic Web - PADS Implications for the Dynamic Web , 2006, 20th Workshop on Principles of Advanced and Distributed Simulation (PADS'06).

[21]  Bernard P. Zeigler,et al.  Multifaceted, multiparadigm modeling perspectives: tools for the 90's , 1986, WSC '86.

[22]  Leslie S. Winters,et al.  Composable M&S Web Services for Net-Centric Applications , 2006 .