Agent-Based Service-Oriented Architecture for Heterogeneous Data Sources Management in Ubiquitous Enterprise

Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

In a ubiquitous manufacturing environment, different devices such as radio frequency identification (RFID) technology are used to collect real-time data. Additionally, data is used by different enterprise information systems for supporting managerial decision making. Since data sources from applications and devices are characterized by multiple types of heterogeneities such as communication channels, blinding methods, and developing environments, the difficulty in managing heterogeneous data sources is greatly increased. This paper proposes an innovative Application Information Service (AIS) that serves as a middleware for information exchange in between different applications. The AIS possesses several key contributions. Firstly, AIS provides a centralized platform to manage distributed heterogeneous data sources so as to reduce the data duplications, increase consistency, and accuracy. Secondly, it combines software agent technologies with service-oriented architecture (SOA) so that services are capable of accomplishing tasks in an autonomous way without human intervention. Thirdly, agent-based service-oriented architecture paradigm is proposed to cultivate a collaborative environment to integrate different data sources as well as third party application providers.

Notes

Acknowledgments

Authors are grateful to the Zhejiang Provincial, Hangzhou Municipal and Lin’an City governments for partial financial supports. HKSAR RGC GRF HKU 712112E, Guangdong Modern Information Service Fund 2009 (GDIID2009IS048), 2010 Guangdong Department of Science and Technology Funding (2010B050100023), and International Collaborative Project of Guangdong High Education Institution (gjhz1005).

References

  1. 1.
    Mohsen A (2007) RFID: an enabler of supply chain operations. Supply Chain Manag Int J 12(4):249–257CrossRefGoogle Scholar
  2. 2.
    Halevy AY et al (2005) Enterprise information integration: successes, challenges and controversies. In: Proceedings of the 2005 ACM SIGMOD international conference on management of data 2005, ACM, Baltimore, pp 778–787Google Scholar
  3. 3.
    Sujansky W (2001) Heterogeneous database integration in biomedicine. Comput Biomed Res 34(4):285–298Google Scholar
  4. 4.
    Halevy A, Rajaraman A, Ordille J (2006) Data integration: the teenage years. in VLDB’2006: Proceedings of the 32nd international conference on very large data bases. VLDB EndowmentGoogle Scholar
  5. 5.
    Ronald EG (2004) A framework to review the information integration of the enterprise. Int J Prod Res 42(6):1147–1166MATHCrossRefGoogle Scholar
  6. 6.
    Lenzerini M (2002) Data integration: a theoretical perspective. In: Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on principles of database systems, ACM, Madison, Wisconsin, pp 233–246Google Scholar
  7. 7.
    Woelk D et al (1993) Using Carnot for enterprise information integration. In parallel and distributed information systems. In: Proceedings of the second international conference on 1993Google Scholar
  8. 8.
    Gorton I, Liu A (2004) Architectures and technologies for enterprise application integration. In: Software engineering, ICSE 2004 Proceedings of 26th international conference on 2004Google Scholar
  9. 9.
    Sikora R, Shaw MJ (1998) A multi-agent framework for the coordination and integration of information systems. Manage Sci 44(11):S65–S78MATHCrossRefGoogle Scholar
  10. 10.
    Gek Woo T, Hayes CC, Shaw M (1996) An intelligent-agent framework for concurrent product design and planning. Eng Manag IEEE Trans 43(3):297–306Google Scholar
  11. 11.
    Jiao J, You X, Kumar A (2006) An agent-based framework for collaborative negotiation in the global manufacturing supply chain network. Robot Comput Integr Manuf 22(3):239–255CrossRefGoogle Scholar
  12. 12.
    Bastos RM, de Oliveira FM, de Oliveira JPM (2005) Autonomic computing approach for resource allocation. Expert Syst Appl 28(1):9–19CrossRefGoogle Scholar
  13. 13.
    Weiming S, Lihui W, Qi H (2006) Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey. Syst Man Cyber C Appl Rev IEEE Trans 36(4):563–577Google Scholar
  14. 14.
    Bayardo RJ et al (1997) Info Sleuth: agent-based semantic integration of information in open and dynamic environments. SIGMOD Rec 26(2):195–206Google Scholar
  15. 15.
    http://www.fipa.org. Accessed May 2012
  16. 16.
    Bellifemine F, Rimassa G (2001) Developing multi-agent systems with a FIPA-compliant agent framework. Softw Pract Exper 31(2):103–128MATHCrossRefGoogle Scholar
  17. 17.
    Huhns MN (2002) Agents as web services. Int Comput IEEE 6(4):93–95CrossRefGoogle Scholar
  18. 18.
    Dale J et al (2003) Implementing agent-based web services. In: AAMAS 2003 workshop on challenges in open agent environments, Melbourne Australia. CiteseerGoogle Scholar
  19. 19.
    Huhns M (2003) Software agents: the future of web services. In: Carbonell et al J (ed) agent technologies, infrastructures, tools, and applications for E-services, Springer, Berlin, pp 1–18Google Scholar
  20. 20.
    Brazier FMT et al (2009) Agents and service-oriented computing for autonomic computing: a research agenda. Int Comput IEEE 13(3):82–87CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems EngineeringThe University of Hong KongHong Kong SARChina

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