Abstract
It is well known that grid technology has the ability to realize the resources shared and tasks scheduled coordinately. However, the problem of resource management and scheduling has always been one of main challenges. Recently, the theory of grid economy, which is analogous to the real market-based economy, can become a good candidate for solving the problem efficiently. But, in grid economy, the decision problem of resources selection with portfolio optimization has been paid little attention to. In this paper, the portfolio model and algorithm for dynamic multi-stage resource selection with preference factors were provided, analyzed and explained based on the grid economy in detail. The results of the experiments proved that corresponding methods were feasible and efficient in dynamic and distributed environments.
The works were supported by Nation High Technology 863 Development Plan (Grant No 2003AA001032), Open Fund from National Key Laboratory in Software Engineering (SKLSE03-14), Key Technologies R&D Program of Hubei Province (Grant No.211130757).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Rajkumar, B., David, A., Srikumar, V.: The Grid Economy. Proceedings of the IEEE 3, 698–714 (2005)
Zhongfei, L., Shouyang, W.: Portfolio Optimization and No-Arbitrage Analysis, vol. 5. Science Publisher (2001)
Hiroshi, K., Annista, W.: Portfolio Optimization Problem under Concave Transaction Costs and Minimal Transaction Unit Constraints. Math. Program. 9, 233–250 (2001)
Markowitz, H.: Portfolio Selection Efficient Diversification of Investment. Wiley, New York (1959)
Wlodzimierz, O.: Multiple Criteria Linear Programming Model for Portfolio Selection. Annual of Operations Research, 143–162 (2000)
Edwin, J.E., Martin, J.G., Jeffrey, A.B.: Are Investors Rational Choices Among Index Funds. Journal of Finance 59(2) (2004)
Chris, K., Giorgos, C.: Grid Resource Commercialization Economic Engineering and Delivery Scenarios. Grid Resource Management: State of the Art and Research Issues. Kluwer, Dordrecht (2003)
Chris, K., Giorgos, C.: Architecture Requirements for Commercializing Grid Resources. In: Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing, vol. 7, pp. 215–224 (2002)
Hua, Y., Wu, C., Xing, J.: Grid QoS Infrastructure: Advance Resource Reservation in Optical Burst Switching Networks. In: Jin, H., Pan, Y., Xiao, N., Sun, J. (eds.) GCC 2004. LNCS, vol. 3251, pp. 979–982. Springer, Heidelberg (2004)
Buyya, R., Abramson, D., Giddy, J.: A Case for Economy Grid Architecture for Service-Oriented Grid Computing. In: Proceedings of the 15th International Conference on Parallel and Distributed Processing Symposium, vol. 4, pp. 776–790 (2001)
Yoshimoto, A.: The Mean-Variance Approach to Portfolio Optimization Subject to Transaction Costs. Journal of the Operations Research Society of Japan, 99–117 (1996)
Simaan, Y.: Estimation Risk in Portfolio Selection The Mean Variance Model Versus The Mean Absolute Deviation Model. Management Science, 1437–1446 (1997)
Zhang, Y., Hua, Y.: Portfolio optimization for multi-stage capital investment with neural networks. In: Yin, F.-L., Wang, J., Guo, C. (eds.) ISNN 2004. LNCS, vol. 3174, pp. 982–987. Springer, Heidelberg (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hua, Y., Wu, C. (2005). Dynamic Multi-stage Resource Selection with Preference Factors in Grid Economy. In: Zhuge, H., Fox, G.C. (eds) Grid and Cooperative Computing - GCC 2005. GCC 2005. Lecture Notes in Computer Science, vol 3795. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11590354_84
Download citation
DOI: https://doi.org/10.1007/11590354_84
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30510-1
Online ISBN: 978-3-540-32277-1
eBook Packages: Computer ScienceComputer Science (R0)