Defining a Semantic Web-based Framework for Enabling Automatic Reasoning on CIM-based Management Platforms Fernando Alonso, Rafael Fern´ andez, Sonia Frutos, and Javier Soriano Abstract— CIM is the standard formalism for modeling manage- ment information developed by the Distributed Management Task Force (DMTF) in the context of its WBEM proposal, designed to provide a conceptual view of the managed environment. In this paper, we propose the inclusion of formal knowledge representation techniques, based on Description Logics (DLs) and the Web Ontology Language (OWL), in CIM-based conceptual modeling, and then we examine the benefits of such a decision. The proposal is specified as a CIM metamodel level mapping to a highly expressive subset of DLs capable of capturing all the semantics of the models. The paper shows how the proposed mapping provides CIM diagrams with precise semantics and can be used for automatic reasoning about the management information models, as a design aid, by means of new- generation CASE tools, thanks to the use of state-of-the-art automatic reasoning systems that support the proposed logic and use algorithms that are sound and complete with respect to the semantics. Such a CASE tool framework has been developed by the authors and its architecture is also introduced. The proposed formalization is not only useful at design time, but also at run time through the use of rational autonomous agents, in response to a need recently recognized by the DMTF. Keywords— CIM, Knowledge-based Information Models, Ontol- ogy Languages, OWL, Description Logics, Integrated Network Man- agement, Intelligent Agents, Automatic Reasoning Techniques. I. I NTRODUCTION T HE growing complexity, heterogeneity and dynamism inherent in emerging telecommunications networks, dis- tributed systems and advanced information and communica- tion services, as well as their increased criticality and strategic importance in the networked economy, calls for the adoption of increasingly more sophisticated technologies for their man- agement, coordination and integration to assure adequate levels of functionality, performance and reliability. Of the available technologies, those associated with the autonomous agent-based computation paradigm [16], [10] are precisely the ones that are better accepted for conceiving new techniques for developing management solutions with a higher level of automation, greater potential for interop- erability within open environments and better capabilities of cooperation. Autonomous agent technology and, particularly, Multi-Agent Systems provide in this respect a series of new Manuscript received March 28, 2006. This work is being supported in part by the Spanish Ministry of Science and Technology (contract TIC2001- 3451); and the Spanish Ministry of Industry, Tourism and Commerce under its National Program of Service Technologies for the Information Society (contract FIT-350110-2005-73). F.Alonso, R. Fern´ andez, S.Frutos and J.Soriano are with the with Depart- ment of Computer Science, Technical University of Madrid (UPM), Spain. (e-mail: {falonso,sfrutos,jsoriano}@fi.upm.es, rfdez@pegaso.ls.fi.upm.es) and exciting possibilities in the field of network operations and management [6], [7], such as formal semantic-level knowl- edge representation, automatic reasoning and learning capa- bilities, high-level communication languages and protocols, frameworks for automated negotiation, goal-driven proactive behavior or rational decision making. The formalisms used in management information modeling and representation are closely related to the capabilities of automation, interoperation and cooperation of the management solutions developed on their basis. The success of the process of incorporating autonomous agents, capable of reasoning and dynamically integrating knowledge and services, as an enabling technology for new management solutions, largely depends on the evolution of the information models of existing management architectures [8] towards explicit declarative-type semantic models, equipped with a solid formal basis, that can capture the semantics of the management information models, as well as their formal specification, communication and automatic reasoning about these models. Knowledge Rep- resentation and Conceptual Modeling [1] are the fields of Artificial Intelligence that have progressed most in this respect. However, they have had hardly any impact on any of the management information models built to date. Considering the advances achieved in the field of Knowl- edge Representation by the international research community, the strategy followed for building the existing management information models should be reconsidered and the possibility of including techniques related to the field of Knowledge Representation should be examined, as should the benefits of such a decision. In this paper, we demonstrate the adequacy of the use of Description Logics [11] and the Web Ontology Language OWL [18] for formally defining the structure and constraints of management information in the context of the information model of a management architecture.This model determines the modelling approach and notation used to de- scribe the managed elements, which includes their identifica- tion, structure, behavior and relations to other elements. Common Information Model (CIM) is the chosen infor- mation model. CIM is the standard formalism for modeling management information developed by the Distributed Man- agement Task Force DMTF in the context of its WBEM proposal [2], designed to provide a conceptual view of the managed environment. There is widespread agreement on the need to provide CIM diagrams with precise semantics that can be used to establish a common understanding of the formal meaning of the CIM metamodel constructs used for World Academy of Science, Engineering and Technology International Journal of Computer and Information Engineering Vol:2, No:2, 2008 555 International Scholarly and Scientific Research & Innovation 2(2) 2008 scholar.waset.org/1307-6892/4206 International Science Index, Computer and Information Engineering Vol:2, No:2, 2008 waset.org/Publication/4206