Abstract
In Utility Computing business model, the owners of the computing resources negotiate with their potential clients to sell computing power. The terms of the Quality of Service (QoS) to be provided as well as the economic conditions are established in a Service-Level Agreement (SLA). There are situations in which providers must differentiate the SLAs in function of the type of Client that is willing to access the resources or the agreed QoS e.g. when the hardware resources are shared between users of the company that own the resources and external users.
This paper proposes to consider the information of potential users when the SLA is under negotiation to allow providers to prioritize users (e.g. internal users over external users, or preferential users over common users). Two policies for negotiation are introduced: price discrimination and client-aware overselling of resources. The validity of the policies is demonstrated through exhaustive experiments.
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References
Amazon EC2 instances, http://aws.amazon.com/ec2/instance-types/ (last visit: February 2011)
Client classification and reclassification policy of rabobank polska sa, http://goo.gl/AKu86 (last visit: February 2011)
Drools rule engine, http://www.jboss.org/drools
Economically Enhanced Resource Manager, http://www.sf.net/projects/eerm (last visit: August 2011)
Spotify, http://www.spotify.com
Windows azure, http://www.microsoft.com/windowsazure/ (last visit: February 2011)
Barford, P., Crovella, M.: Generating representative web workloads for network and server performance evaluation. In: 1998 ACM SIGMETRICS Joint International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS 1998/PERFORMANCE 1998), vol. 26, pp. 151–160. ACM Press, Madison (1998)
Buyya, R., Yeo, C.S., Venugopal, S.: Market-oriented cloud computing: Vision, hype, and reality for delivering it services as computing utilities. In: 10th IEEE Intl. Conf. on High Performance Computing and Communications (HPCC 2008), pp. 5–13. IEEE Computer Society, Dalian (2008)
Choong, H.L., Jinwoo, S., Kyoungmin, P.: Grid and p2p economics and market models. In: I.C. Society (ed.) 1st IEEE International Workshop on Grid Economics and Business Models (GECON 2004), Seoul, South Korea, pp. 3–18 (April 2004)
Dube, P., Hayel, Y., Wynter, L.: Yield management for IT resources on demand: analysis and validation of a new paradigm for managing computing centres. Journal of Revenue and Pricing Management 4(1), 24–38 (2005)
Foster, I.: The anatomy of the grid: Enabling scalable virtual organizations. In: IEEE International Symposium on Cluster Computing and the Grid, p. 6 (2001)
Goiri, Í., Julià, F., Fitó, J.O., Macías, M., Guitart, J.: Resource-Level QoS Metric for CPU-Based Guarantees in Cloud Providers. In: Altmann, J., Rana, O.F. (eds.) GECON 2010. LNCS, vol. 6296, pp. 34–47. Springer, Heidelberg (2010)
Kaufman, L.M.: Data security in the world of cloud computing. IEEE Security and Privacy 7, 61–64 (2009)
Lee, H.Y., Choo, T.T., Khee-Erng, J.L., Wong, W.: A grid market framework. In: 3rd International Workshop on Grid Economics and Business Models (GECON 2006), Singapore, pp. 70–79 (May 2006)
Macias, M., Fito, O., Guitart, J.: Rule-based sla management for revenue maximisation in cloud computing markets. In: 2010 Intl. Conf. of Network and Service Management (CNSM 2010), Niagara Falls, Canada, pp. 354–357 (October 2010)
Macias, M., Guitart, J.: Using resource-level information into nonadditive negotiation models for cloud market environments. In: 12th IEEE/IFIP Network Operations and Management Symposium (NOMS 2010), Osaka, Japan, pp. 325–332 (April 2010)
Porter, M.E.: Clusters and the new economics of competition. Harvard Business Review 76(6), 77–90 (1998)
Püschel, T., Borissov, N., Macías, M., Neumann, D., Guitart, J., Torres, J.: Economically Enhanced Resource Management for Internet Service Utilities. In: Benatallah, B., Casati, F., Georgakopoulos, D., Bartolini, C., Sadiq, W., Godart, C. (eds.) WISE 2007. LNCS, vol. 4831, pp. 335–348. Springer, Heidelberg (2007)
Rappa, M.A.: The utility business model and the future of computing services. IBM Syst. J. 43(1), 32–42 (2004)
Reig, G., Alonso, J., Guitart, J.: Prediction of job resource requirements for deadline schedulers to manage high-level slas on the cloud. In: 9th IEEE Intl. Symp. on Network Computing and Applications, Cambridge, MA, USA, pp. 162–167 (July 2010)
Sandholm, T., Lai, K.: Evaluating demand prediction techniques for computational markets. In: 3rd International Workshop on Grid Economics and Business Models (GECON 2006), Singapore, pp. 3–13 (May 2006)
Sulistio, A., Kim, K.H., Buyya, R.: Managing cancellations and no-shows of reservations with overbooking to increase resource revenue. In: Intl. Symp. on Cluster Computing and the Grid (CCGRID 2008), pp. 267–276. IEEE Computer Society, Lyon (2008)
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Macías, M., Guitart, J. (2012). Client Classification Policies for SLA Negotiation and Allocation in Shared Cloud Datacenters. In: Vanmechelen, K., Altmann, J., Rana, O.F. (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2011. Lecture Notes in Computer Science, vol 7150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28675-9_7
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DOI: https://doi.org/10.1007/978-3-642-28675-9_7
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