Agent-Based Service-Oriented Architecture for Heterogeneous Data Sources Management in Ubiquitous Enterprise
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.
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).
- 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.Sujansky W (2001) Heterogeneous database integration in biomedicine. Comput Biomed Res 34(4):285–298Google Scholar
- 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
- 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.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.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
- 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
- 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.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.http://www.fipa.org. Accessed May 2012
- 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.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