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Issue No.01 - Jan. (2014 vol.25)
pp: 12-21
Nancy Samaan , University of Ottawa, Ottawa
ABSTRACT
This paper presents a novel economic model to regulate capacity sharing in a federation of hybrid cloud providers (CPs). The proposed work models the interactions among the CPs as a repeated game among selfish players that aim at maximizing their profit by selling their unused capacity in the spot market but are uncertain of future workload fluctuations. The proposed work first establishes that the uncertainty in future revenue can act as a participation incentive to sharing in the repeated game. We, then, demonstrate how an efficient sharing strategy can be obtained via solving a simple dynamic programming problem. The obtained strategy is a simple update rule that depends only on the current workloads and a single variable summarizing past interactions. In contrast to existing approaches, the model incorporates historical and expected future revenue as part of the virtual machine (VM) sharing decision. Moreover, these decisions are not enforced neither by a centralized broker nor by predefined agreements. Rather, the proposed model employs a simple grim trigger strategy where a CP is threatened by the elimination of future VM hosting by other CPs. Simulation results demonstrate the performance of the proposed model in terms of the increased profit and the reduction in the variance in the spot market VM availability and prices.
INDEX TERMS
Resource management, Games, History, Availability, Adaptation models, Economics, Uncertainty,subgame perfect equilibrium, Cloud federation, cloud provider, capacity outsourcing, repeated game
CITATION
Nancy Samaan, "A Novel Economic Sharing Model in a Federation of Selfish Cloud Providers", IEEE Transactions on Parallel & Distributed Systems, vol.25, no. 1, pp. 12-21, Jan. 2014, doi:10.1109/TPDS.2013.23
REFERENCES
[1] R. Buyya, C.S. Yeo, S. Venugopal, J. Broberg, and I. Brandic, "Cloud Computing and Emerging it Platforms: Vision, Hype, and Reality for Delivering Computing as the Fifth Utility," Future Generation Computer Systems, vol. 25, no. 6, pp. 599-616, 2009.
[2] M. Armbrust et al., "A View of Cloud Computing," Comm. ACM, vol. 53, no. 4, pp. 50-58, 2010.
[3] Í Goiri, F. Julià, J. Oriol Fitó, M. Macías, and J. Guitart, "Supporting CPU-Based Guarantees in Cloud SLAs Via Resource-Level QoS Metrics," Future Generation Computer Systems, vol. 28, no. 8, pp. 1295-1302, Oct. 2012.
[4] M. Mattess, C. Vecchiola, and R. Buyya, "Managing Peak Loads by Leasing Cloud Infrastructure Services from a Spot Market," Proc. IEEE 12th Int'l Conf. High Performance Computing and Communications (HPCC), pp. 180-188, 2010.
[5] Amazon EC2, http://aws.amazon.comec2/, Dec. 2011.
[6] J. Chen, C. Wang, B. Zhou, L. Sun, Y. Lee, and A.Y. Zomaya, "Tradeoffs between Profit and Customer Satisfaction for Service Provisioning in the Cloud," Proc. 20th Int'l Symp. High Performance Distributed Computing (HPDC), pp. 229-238, 2011.
[7] B. Rochwerger, D. Breitgand, A. Epstein, D. Hadas, I. Loy, K. Nagin, J. Tordsson, C. Ragusa, M. Villari, S. Clayman, E. Levy, A. Maraschini, P. Massonet, H. Muñoz, and G. Toffetti, "Reservoir—When One Cloud is Not Enough," Computer, vol. 44, no. 3, pp. 44-51, Mar. 2011.
[8] B. Rochwerger, E. Levy, A. Galis, K. Nagin, I.M. Llorente, R. Montero, Y. Wolfsthal, E. Elmroth, J. Caceres, M. Ben-Yehuda, W. Emmerich, and F. Galan, "The Reservoir Model and Architecture for Open Federated Cloud Computing," IBM J. Research and Development, vol. 53, no. 4, pp. 1-11, July 2009.
[9] K. Le, R. Bianchini, J. Zhang, Y. Jaluria, J. Meng, and T. Nguyen, "Reducing Electricity Cost through Virtual Machine Placement in High Performance Computing Clouds," Proc. Int'l Conf. High Performance Computing, Networking, Storage and Analysis (SC '11), pp. 1-12, 2011.
[10] Í Goiri, J. Guitart, and J. Torres, "Economic Model of a Cloud Provider Operating in a Federated Cloud," Information Systems Frontiers, vol. 12, pp. 827-843, 2012.
[11] A. Avetisyan et al., "Open Cirrus: A Global Cloud Computing Testbed," Computer, vol. 43, no. 4, pp. 35-43, Apr. 2010.
[12] A. Toosi, R. Calheiros, R. Thulasiram, and R. Buyya, "Resource Provisioning Policies to Increase IaaS Provider's Profit in a Federated Cloud Environment," Proc. IEEE 13th Int'l Conf. High Performance Computing and Communications (HPCC), pp. 279-287, 2011.
[13] Q. Zhang, E. Gürses, R. Boutaba, and J. Xiao, "Dynamic Resource Allocation for Spot Markets in Clouds," Proc. 11th USENIX Conf. Hot Topics in Management of Internet, Cloud, and Enterprise Networks and Services (Hot-ICE '11), 2011.
[14] E. Gomes, Q. Vo, and R. Kowalczyk, "Pure Exchange Markets for Resource Sharing in Federated Clouds," Concurrency and Computation: Practice and Experience, vol. 24, no. 9, pp. 977-991, 2012.
[15] M. Mihailescu and Y. Teo, "Dynamic Resource Pricing on Federated Clouds," Proc. 10th IEEE/ACM Int'l Conf. Cluster, Cloud and Grid Computing (CCGrid), pp. 513-517, 2010.
[16] Y.C. Lee, C. Wang, A.Y. Zomaya, and B.B. Zhou, "Profit-Driven Service Request Scheduling in Clouds," Proc. 10th IEEE/ACM Int'l Conf. Cluster, Cloud and Grid Computing (CCGrid), pp. 15-24, 2010.
[17] R. Van den Bossche, K. Vanmechelen, and J. Broeckhove, "Cost-Optimal Scheduling in Hybrid IaaS Clouds for Deadline Constrained Workloads," Proc. IEEE Third Int'l Conf. Cloud Computing (CLOUD), pp. 228-235, 2010.
[18] S. Chaisiri, B. Lee, and D. Niyato, "Optimization of Resource Provisioning Cost in Cloud Computing," IEEE Trans. Services Computing, vol. 5, no. 2, pp. 164-177, Apr.-June 2012.
[19] R. Wolski, J. Plank, J. Brevik, and T. Bryan, "Analyzing Market-Based Resource Allocation Strategies for the Computational Grid," Int'l J. High Performance Computing Applications, vol. 15, no. 3, pp. 258-281, 2001.
[20] X. Bai, D. Marinescu, L. Bölöni, H. Jay Siegel, R. Daley, and I. Wang, "A Macroeconomic Model for Resource Allocation in Large-Scale Distributed Systems," J. Parallel and Distributed Computing, vol. 68, no. 2, pp. 182-199, 2008.
[21] W. Streitberger and T. Eymann, "A Simulation of an Economic, Self-Organising Resource Allocation Approach for Application Layer Networks," Computer Networks, vol. 53, no. 10, pp. 1760-1770, 2009.
[22] M. Mazzucco and M. Dumas, "Reserved or On-Demand Instances? A Revenue Maximization Model for Cloud Providers," Proc. IEEE Int'l Conf. Cloud Computing (CLOUD) pp. 428-435, 2011.
[23] B. Sotomayor, R.S. Montero, I.M. Llorente, and I. Foster, "Virtual Infrastructure Management in Private and Hybrid Clouds," IEEE Internet Computing, vol. 13, no. 5, pp. 14-22, Sept./Oct. 2009.
[24] S. Pacheco-Sanchez, G. Casale, B.W. Scotney, S.I. McClean, G.P. Parr, and S. Dawson, "Markovian Workload Characterization for QoS Prediction in the Cloud," Proc. IEEE Int'l Conf. Cloud Computing (CLOUD), pp. 147-154, 2011.
[25] Z. Gong, X. Gu, and J. Wilkes, "Press: Predictive Elastic Resource Scaling for Cloud Systems," Proc. Int'l Conf. Network and Service Management (CNSM), pp. 9-16, 2010.
[26] S. Maguluri, R. Srikant, and L. Ying, "Stochastic Models of Load Balancing and Scheduling in Cloud Computing Clusters," IEEE INFOCOM, 2012.
[27] W. Wong and J. Davis, "Boostpred: An Automatic Demand Predictor for the Cloud," Proc. IEEE Ninth Int'l Conf. Dependable, Autonomic and Secure Computing (DASC), pp. 411-418, 2011.
[28] H. Khazaei, J. Misic, and V. Misic, "Performance Analysis of Cloud Computing Centers Using M/G/m/m + r Queueing Systems," IEEE Trans. Parallel and Distributed Systems, vol. 3, no. 5, pp. 936-943, May 2012.
[29] D. Fudenberg and J. Tirole, Game Theory, MIT Press, 1991.
[30] L. Ljungqvist and T. Sargent, Recursive Macroeconomic Theory, second ed., MIT Press, 2004.
[31] E. Ligon, J. Thomas, and T. Worrall, "Mutual Insurance, Individual Savings, and Limited Commitment," Rev. of Economic Dynamics, vol. 3, no. 2, pp. 216-246, 2000.
[32] D. Bertsekas, Dynamic Programming and Stochastic Control, vol. 125, Academic Press, 1976.
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