Study on the Architecture for Agricultural Products Quantity Security Early Warning System

Abstract:

The early warning system for agricultural products quantity security requires storing and analyzing massive agricultural data. These data is of huge amount, heterogeneous, and has a wide-ranging source, thus the system should have an effective data collection mechanism. Based on all these requirements, how to construct an efficient early warning system has become a primary problem. In this paper, we focused our research on the architecture of the early warning system, and divided the system into application system, data collection system, and persistence system. Then we put forward reasonable architecture for each of them based on Web service and data warehouse. Finally, we emphasized on the discussion on the process of acquiring data from ministries based on the use of Web service adaptation technology. The proposed architectures are with fine flexibility and robustness, so they could be effectively used on the construction of the early warning system.

• Periodical: Advanced Materials Research (Volumes 108-111)
• Pages: 228-233
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.108-111.228
• Online since: May 2010
• Authors: Shu Dong Zhang, N.M. Yao, Y. Qin
• Keywords: Agriculture, Architecture, Early Warning System, Web Service Adaptation

References

[1] Information on http: /www. fao. org/giews/english.

[2] Information on http: /www. agry. purdue. edu.

[3] S. Yasunori, S. Takanobu and K. Kinichi: Proceeding of SICE-ICASE International Joint Conference (2006), pp.4848-4851.

[4] Information on http: /www. ers. usda. gov/briefing/Baseline.

[5] R.M. Adams, L. L Houston and B.A. McCarl and M. Tiscareno, J. Matus and R.F. Weiher: Agricultural and Forest Meteorology Vol. 115 (2003), pp.183-194.

DOI: 10.1016/s0168-1923(02)00201-0

[6] V. Valentin, M.E. Cambronero, D. Gregorio and M. Hermenegilda: Journal of Logic and Algebraic Vol. 78 (2009), pp.359-380.

[7] F. You, Q.X. Hu, Y. Yao and Q. Lu: Key Eng. Mat. Vol. 392-394 (2009), pp.634-639.

[8] S. Mitra, R. Kumar and S. Basu: Proceeding of International Conference on Services Computing (2008), pp.395-402.

[9] D. Burdick, P.M. Deshpande, T.S. Jayram, R. Ramakrishnan and S. Vaithyanathan: Proceedings of 31st International Conference on Very Large Data Bases (2005), pp.970-981.

[10] V. Panos: International Journal of Data Warehousing and Mining Vol. 5 (2009), pp.1-27.

[11] B. Benatallah, F. Casati and D. Grigori: Lect. Notes Comput. Sci. Vol. 3520 (2005), pp.415-429.

[12] W. Kongdenfha, H.R.M. Nezhad and B. Benatallah: IEEE Transactions on Services Computing Vol. 2 (2009), pp.94-107.

[13] S.D. Zhang, Y. Qin and N.M. Yao: submitted to Journal of Key Engineering Materials (2010).

[14] Z. Covacheva: Proceedings of the 4th International Conference on Computer Systems and Technologies (2003), pp.113-118.