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Grid resources pricing: A novel financial option based quality of service-profit quasi-static equilibrium model

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R. K. ThulasiramAuthors Info & Claims

GRID '08: Proceedings of the 2008 9th IEEE/ACM International Conference on Grid Computing

Pages 75 - 84

https://doi.org/10.1109/GRID.2008.4662785

Published: 29 September 2008 Publication History

Abstract

Use of grid resources has been free so far and a trend is developing to charge the users. The challenges that characterize a grid resource pricing model include the dynamic ability of the model to provide a high satisfaction guarantee measured as quality of service (QoS) - from users perspectives, profitability constraints - from the grid operator perspectives, and the ability to orchestrate grid resources for their availability on-demand. In this study, we design, develop, and simulate a grid resources pricing model that balances these constraints. We employ financial option theory and treat the grid resources as real assets to capture the realistic value of the grid compute commodities. We then price the grid resources by solving the finance model. We discuss the results on pricing of compute cycles based on the actual data of grid usage pattern obtained from the WestGrid and the SHARCNET. We extend and generalize our study to any computational grid.

References

[1]

D. Allenotor and R. K. Thulasiram. A Real Option Model for Pricing Grid Computing Resources and QoS. In A Poster in Grid 2007, Austin, TX, USA, Sept. 19-21, 2007.

[2]

D. Allenotor and R. K. Thulasiram. G-FRoM: Grid Resources Pricing A Fuzzy Real Option Model. In Proc. 3rd Int' Conference on e-Science and Grid Computing (eScience 2007) Bangalore, India, December 10-13, 2007.

Digital Library

[3]

M. Amico, Z. J. Pasek, F. Asl, and G. Perrone. Simulation Methodology For Collateralized Debt and Real Options: A New Methodology to Evaluate The Real Options of Investment Using Binomial Trees and Monte Carlo Simulation. In Winter Simulation Conference '03: Proceedings of the 35th Conference on Winter Simulation, 2003.

Digital Library

[4]

H. K. Bhargava and S. Sundaresan. Contingent bids in auctions: Availability, commitment and pricing of computing as utility. In HICSS 2004: Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 8, 2004.

Digital Library

[5]

F. Black and Scholes. The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 1973.

[6]

G. Bojadziew and M. Bojadziew. Fuzzy Logic for Business, Finance, and Management Modeling. World Scientific Press, 2nd Edition, 1997.

Digital Library

[7]

P. P. Boyle. Option Valuing Using a Three Jump Process. International Options Journal, 3(2), 1986.

[8]

R. Buyya, D. Abramson, and J. Giddy. A Case for Economy Grid Architecture for Service Oriented Grid Computing. In IPDPS 2001: Proceedings of the 10th Heterogeneous Computing Workshop & #226 HCW 2001 (Workshop 1), 2001.

Digital Library

[9]

R. Buyya, D. Abramson, and S. Venugopal. The Grid Economy. In IEEE Journal, 2005.

[10]

R. Buyya, J. Giddy, and D. Abramson. An evaluation of Economy-based Resource Trading and Scheduling on Computational Power Grids for Parameter Sweep Applications. In Proceedings of the 2nd Workshop on Active Middleware Services, Pittsburgh, USA, August 2000.

[11]

C. Carlsson and R. Fullér. A Fuzzy Approach to Real Option Valuation. Fuzzy Sets and Systems, 39, 2003.

[12]

D. M. Chance and P. P. Peterson. Real Options and Investment Valuation. The Research Foundation of AMIR, First Edition, 2002.

[13]

J. C. Cox, S. Ross, and M. Rubinstein. Option Pricing: A Simplified Approach. Journal of Financial Economics, 7(7), 1979.

[14]

Y. d'Halluin, P. A. Forsyth, and K. R. Vetzal. Managing Capacity For Telecommunications Networks Under Uncertainty. In IEEE/ACM Transaction on Networking, 10(4), 2002.

Digital Library

[15]

I. Foster, C. Kesselman, G. Tsudik, and S. Tuecke. A security Architecture for Computational Grids. In ACM Conference on Computer and Communications Security, pages 83-92, 1998.

Digital Library

[16]

I. Foster, C. Kesselman, and S. Tuecke. The Anatomy of The Grid: Enabling Scalable Virtual Organizations. Int. Journal of Supercomputer Applications, 15(3), 2001.

Digital Library

[17]

A. V. Gerbessiotis. Architecture independent parallel binomial tree option price valuations. Parallel Computing, 30(2), 2004.

Digital Library

[18]

A. A. Gray, P. Arabshahi, E. Lamassoure, C. Okino, and J. Andringa. A Real Option Framework for Space Mission Design. Technical Report Jet Propulsion labouratory, NASA, LAB, Aug. 2004.

[19]

A. Gupta, L. Zhang, and S. Kalyanaraman. Simulation for Risk Management: A Two-component Spot Pricing Framework For Loss-rate Guaranteed Internet Service Contracts. In Winter Simulation Conference '03: Proceedings of the 35th conference on Winter simulation, 2003.

Digital Library

[20]

J. Hull. Options, Futures, and Other Derivatives. Prentice Hall, Sixth Edition, 2006.

[21]

V. Krishna and M. Perry. Efficient mechanism Design, 1998 working paper {online}. Available http://ratio.huji.ac.il/dp/dp133.pdf, 2007.

[22]

A. Mutz, R. Wolski, and J. Brevik. Eliciting Honest Value Information in a Batch-Queue Environment. In The 8th IEEE/ACM International Conference on Grid Computing. September 1921, Austin, Texas, USA., September 2007.

Digital Library

[23]

M. Palankar, A. Onibokun, A. Iamnitchi, and M. Ripeanu. Amazon s3 for science grids: a viable solution? In Poster: 4th USENIX Symposium on Networked Systems Design and Implementation (NSDI'07), April 2007.

[24]

S. Pantry and P. Griffiths. The Complete Guide to Preparing and Implementary Service Level Agreements. Library Association Publishing, First Edition, 1997.

[25]

E. Schwartz. The Valuation of Warrants: Implementing a New Approach. Journal of Financial Economics, 22(4), 2003.

[26]

SHARCNET. Shared Hierarchical Academic Research Computing Network (SHARCNET). Available http://www.sharcnet.ca/Performance/cur_perf.php, April 2008.

[27]

R. K. Thulasiram, L. Litov, H. Nojumi, C. T. Downing, and G. R. Gao. Multithreaded Algorithms for Pricing a Class of Complex Options. In Proceedings (CD-ROM) of the International Parallel and Distributed Processing Symposium (IPDPS), San Francisco, CA, 2001.

Digital Library

[28]

WestGrid. Western Canada Reserach Grid, April 2008.

[29]

R. Wolski, J. Plank, J. Brevik, and T. Bryan. Analyzing Market-Based Resource Allocation Strategies for the Computational Grid. Int. Journal of High Performance Computing Applications, 15(3):285-281, 2001.

Digital Library

[30]

C. S. Yeo and R. Buyya. Integrated risk analysis for a commercial computing service. In Proceedings of the 21st IEEE International Parallel and Distributed Processing Symposium (IPDPS 2007, IEEE CS Press, LosAlamitos, CA, USA), 2007.

[31]

C. S. Yeo and R. Buyya. Integrated Risk Analysis for a Commercial Computing Service. In Proceedings of the 21st IEEE International Parallel and Distributed Processing Symposium (IPDPS 2007, IEEE CS Press, Los Alamitos, CA, USA), 2007.

[32]

L. Zadeh. Fuzzy Sets. Information and Control, 8(4), 1965.

Cited By

Chang V(2014)The Business Intelligence as a Service in the CloudFuture Generation Computer Systems10.1016/j.future.2013.12.02837:C(512-534)Online publication date: 1-Jul-2014
https://dl.acm.org/doi/10.1016/j.future.2013.12.028
Toosi AThulasiram RBuyya R(2012)Financial Option Market Model for Federated Cloud EnvironmentsProceedings of the 2012 IEEE/ACM Fifth International Conference on Utility and Cloud Computing10.1109/UCC.2012.42(3-12)Online publication date: 5-Nov-2012
https://dl.acm.org/doi/10.1109/UCC.2012.42
Sharma BThulasiram RThulasiraman PGarg SBuyya R(2012)Pricing Cloud Compute CommoditiesProceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)10.1109/CCGrid.2012.126(451-457)Online publication date: 13-May-2012
https://dl.acm.org/doi/10.1109/CCGrid.2012.126

Index Terms

Grid resources pricing: A novel financial option based quality of service-profit quasi-static equilibrium model

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cover image Guide Proceedings

GRID '08: Proceedings of the 2008 9th IEEE/ACM International Conference on Grid Computing

September 2008

416 pages

ISBN:9781424425785

Publisher

IEEE Computer Society

United States

Publication History

Published: 29 September 2008

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Cited By

Chang V(2014)The Business Intelligence as a Service in the CloudFuture Generation Computer Systems10.1016/j.future.2013.12.02837:C(512-534)Online publication date: 1-Jul-2014
https://dl.acm.org/doi/10.1016/j.future.2013.12.028
Toosi AThulasiram RBuyya R(2012)Financial Option Market Model for Federated Cloud EnvironmentsProceedings of the 2012 IEEE/ACM Fifth International Conference on Utility and Cloud Computing10.1109/UCC.2012.42(3-12)Online publication date: 5-Nov-2012
https://dl.acm.org/doi/10.1109/UCC.2012.42
Sharma BThulasiram RThulasiraman PGarg SBuyya R(2012)Pricing Cloud Compute CommoditiesProceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)10.1109/CCGrid.2012.126(451-457)Online publication date: 13-May-2012
https://dl.acm.org/doi/10.1109/CCGrid.2012.126

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