Abstract
In order to charge the computer power in the grid, we have made an effort to work towards a standard pricing unit. Currently there is a lot of work done towards the development of grid economy models and architectures. But when it comes to charging, the usual metric which has been popularly used is $ per CPU per Hour which seems to be too simple. Our effort is to make this metric more meaningful to both grid service provider and client. We argue that in a particular grid host the metric should reflect the true load consumed by the clients and the delays caused due to the other loads. Further it should eventually reflect the network, memory etc consumed by the client as well.
Previously we have studied about the prediction in the grid after introducing the division of the load average at the kernel level. This gave more meaning to the historical load collection as CPU historical load data had been collected separately for each login user. Interestingly, later on the division of load strategy has been helpful in the development of a meaningful tariff mechanism and would be demonstrated in this paper.
Eventually this fare mechanism would be used to predict the computational costs, which would certainly contribute to the scheduling in the grid.
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
Buyya, R., Abramson, D., Giddy, J., Stockinger, H.: Economic Models for Resource Management and Scheduling in Grid Computing. Journal of Concurrency: Practice and Experience, Grid computing special issue 14/13-15, 1507–1542 (2002)
Abramson, D., Buuya, R., Giddy, J.: A Computational Economy for Grid Computing and its Implementation in the Nimrod-G Resource Broker. Future Generation Computer Systems 18(8) (October 2002)
Abramson, D., Lewis, A., Peachy, T.: Nimrod/O: A Tool for Automatic Design Optimization. In: The 4th International Conference on Algorithms & Architectures for Parallel Processing (ICA3PP 2000), Hong Kong, December 11-13 (2000)
Liu, C., Yang, L., Foster, I., Angulo, D.: Design and Evaluation of a Resource Selection Framework for Grid Applications. In: Presented at Proceedings of the 11th IEEE International Symposium on High-Performance Distributed Computing (HPDC 11), Edinburgh, Scotland (2002)
Dinda, P.A.: On line Prediction of Running time of Tasks. Journal of Cluster Computing 5 (2002)
Seneviratne, S., Levy, D.: Improving the Measurement of the Load Signal Through More Appropriate Sampling Rate. In: Proceedings of International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA 2004), Las Vegas, Nevada, USA (2004)
Gunther, N.J.: Analyzing Computer Performance. Springer, Heidelberg
Seneviratne, S., Levy, D.: Enhanced Host Load Prediction by Division of User Load Signal for Grid Computing. Submitted to Journal of Cluster Computing
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
Seneviratne, S., Levy, D. (2005). Introduction to a New Tariff Mechanism for Charging for Computer Power in the Grid. In: Hobbs, M., Goscinski, A.M., Zhou, W. (eds) Distributed and Parallel Computing. ICA3PP 2005. Lecture Notes in Computer Science, vol 3719. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564621_37
Download citation
DOI: https://doi.org/10.1007/11564621_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29235-7
Online ISBN: 978-3-540-32071-5
eBook Packages: Computer ScienceComputer Science (R0)