Pricing Services in a Grid of Computers Using Priority Segmentation
Emmanuel Fragniere, Francesco Moresino
DOI: 10.4236/jssm.2010.33040   PDF    HTML     6,848 Downloads   10,349 Views   Citations


In the past decade many grids of computers have been built among non-profit institutions. These grids are built on a voluntary participation and the resources are not charged to the users. When a resource is given free of charge its allocation is in general not optimal. In this paper, we propose an original mechanism that allows an optimal resource allocation without cash exchanges. We develop a pricing scheme where the service is segmented according to the priority level. The optimal prices of the different services are obtained by solving a Markov Decision Process (MDP). Each participant receives a credit that is proportional to its contribution that enables him to have access to services offered by the grid.

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Fragniere, E. and Moresino, F. (2010) Pricing Services in a Grid of Computers Using Priority Segmentation. Journal of Service Science and Management, 3, 345-351. doi: 10.4236/jssm.2010.33040.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] R. Buyya, D. Abramson, and S. Venugopal, “The Grid Economy,” Proceedings of the IEEE, IEEE Press, New York, 2005, Vol. 93, No. 3, pp. 698-714.
[2] S. Das, “Market Mechanism for Grid Computing,” Ph.D. Dissertation, University of Connecticut, 2007.
[3] I. Foster and C. Kesselman, “The Grid: Blueprint for a Future Computing Infrastructure,” Morgan Kaufmann, San Mateo, 1999.
[4] K. Mayer, J. Bowen, and M. Moulton, “A Proposed Model of the Descriptors of Service Process,” Journal of Services Marketing, Vol. 17, No. 6, 2003, pp. 621-639.
[5] J. L. Heskett, W. E. Sasser and C. W. L. Hart, “Service Breakthroughs: Changing the Rules of the Game,” The Free Press, New York, 1990.
[6] E. Fragniere, C. Heitz and F. Moresino, “The Concept of Shadow Price to Monetarize the Intangible Value of Expertise,” IEEE Conference on Service Operations and Logistics, and Informatics, Beijing, 2008, pp. 1736-1741.
[7] K. Lai, “Markets are Dead, Long Live Markets,” Sigecom Exchanges, Vol. 5, No. 4, 2005, pp. 1-10.
[8] K. M. Sim, “A Survey of Bargaining Model for Grid Resource Allocation,” ACM SIGecom Exchanges, Vol. 5, No. 5, 2006, pp. 22-32.
[9] K. M. Sim, “From Market-Driven Agents to Maket-Oriented Grids,” ACM SIGecom Exchanges, Vol. 5, No. 2, 2004, pp. 45-53.
[10] R. Buyya et al., “Economic Models for Resource Mana- gement and Scheduling in Grid Computing,” Journal of Concurrency: Practice and Experience, Vol. 14, No. 13-15, 2002, pp. 1507-1542.
[11] S. K. Garg, S. Venugopal and R. Buyya, “A Meta-schedu- ler with Auction Based Resource Allocation for Global Grids,” 14th IEEE Interna?tional Conference on Parallel and Distributed Systems, Melbourne, 2008, pp. 187-194.
[12] M. Feldman, K. Lai, L. Zhang, “A Price-Anticipating Re- source Allocation Mechanism for Distributed Shared Clusters,” Proceedings of the 6th ACM Conference on Electronic Commerce, Vancouver, 2005, pp. 127-136.
[13] B. Pourebrahimi, S. A. Ostadzadeh, and K. Bertels, “Resource Allocation in Market-Based Grids Using a History-Based Pricing Mechanism,” In: T. Sobh, Ed., Advances in Computer and Information Sciences and Engineering, Springer, 2008, pp. 97-100.
[14] K. Abdelkader, J. Broeckhove and K. Vanmechelen, “Com- modity Resource Pricing in Dynamic Computational Grids,” Proceedings of the IEEE/ACS International Conference on Computer Systems and Applications, Doha, 2008, pp. 422-429.
[15] R. Wolski, J. Plank, J. Brevik, and T. Bryan, “Analyzing Market-Based Resource Allocation Strategies for the Computational Grid,” International Journal of High Performance Computing Applications, Vol. 15, No. 3, 2001, pp. 258-281.
[16] K. Vanmechelen, G. Stuer, and J. Broeckhove, “Pricing Substitutable Grid Resources Using Commodity Market Models,” Proceedings of the 3rd International Workshop on Grid Economics and Business Models, World Scientific, Singapore, 2006, pp. 103-112.
[17] R. K. Thulasiram, “A Grid Resources Pricing Model Based on Financial Option Concept,” Proceedings of 16th International Conference on Advanced Computing and Communications, Chennai, 2008, p. 1.
[18] A. Caracas, “A Pricing Information Service for Grid Com- puting,” Proceedings of the 5th International workshop on Middleware for grid computing, California, 2007.
[19] R. Ranjan, A. Harwood and R. Buyya, “The University of Melbourne Peer-to-Peer-Based Resource Discovery in Global Grids: A Tutorial,” IEEE Communications Surveys & Tutorials, Vol. 10, No. 2, 2008, pp. 6-33.
[20] A. Barmouta, “GridBank: A Grid Accounting Services Architecture (GASA) for Distributed Systems Sharing and Integration,” Proceedings of the International Parallel and Distributed Processing Symposium, Nice, 2003, p. 245a.
[21] M. L. Puterman, “Markov Decision Processes,” Wiley, New York, 1994.
[22] H. J. Kushner and P. G. Dupuis, “Numerical Methods for Stochastic Control Problems in Continuous Time,” Sprin- ger Verlag, New York, 1992.
[23] A. Haurie and F. Moresino, “Two-Time Scale Controlled Markov Chains: A Decomposition and Parallel Processing Approach”, IEEE Transactions on Automatic Control, Vol. 52, No. 12, 2007, pp. 2325-2331.

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