Abstract
The large-granularity software component is the basis for structuring complex enterprise software system. However, current components are small, and their coupling is close. Furthermore, a software entity is broken up and distributed in tiers, and different entity pieces in same level are interweaved. All these limitations lead to unclear component boundary, complicated internal structure and inflexible interaction, which increase difficulties for component to be updated, replaced and maintained. This paper proposes a Multi-agent (M-Agent) component formal method, which encapsulates the enterprise subject domain in the enterprise entity component, encapsulates the enterprise subject process in the intelligent connector, and dynamically assembles them in P2P nodes. The theoretical analysis proves that the proposed method will change enterprise intelligence component to a large granularity, loose coupling and independent evolvement grid component model.
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A. Zaidat, X. Boucher, and L. Vincent: A framework for organization network engineering and integration, Robotics and Computer-Integrated Manufacturing.Volume 21, pp.259–271, (2005)
B.R. Lea, C. Mahesh, W. Gupta, and B. Yu, A prototype multi-agent ERP system: an integrated architecture and a conceptual, Technovation.Volume 25, pp.433–441. (2005)
M. Verwijmeren: Software component architecture in supply chain management, Computersin Industry.Volume 53, pp.165–178, (2004)
Y. Zhang and C. Fang, Active Services: Concepts, Architecture and Implementation(Science publish house: Beijing, 2005)
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© 2007 IFIP International Federation for Information Processing
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Fan, R., Peng, L. (2007). Modeling Enterprise Intelligence Component Based on Multi-Agents. In: Xu, L.D., Tjoa, A.M., Chaudhry, S.S. (eds) Research and Practical Issues of Enterprise Information Systems II. IFIP — The International Federation for Information Processing, vol 254. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-75902-9_49
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DOI: https://doi.org/10.1007/978-0-387-75902-9_49
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4757-0563-8
Online ISBN: 978-0-387-75902-9
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