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Distributed resource allocation is a very important and complex problem in emerging horizontal dynamic cloud federation (HDCF) platforms, where different cloud providers (CPs) collaborate dynamically to gain economies of scale and enlargements of their virtual machine (VM) infrastructure capabilities in order to meet consumer requirements. HDCF platforms differ from the existing vertical supply chain federation (VSCF) models in terms of establishing federation and dynamic pricing. There is a need to develop algorithms that can capture this complexity and easily solve distributed VM resource allocation problem in a HDCF platform. In this paper, we propose a cooperative game-theoretic solution that is mutually beneficial to the CPs. It is shown that in non-cooperative environment, the optimal aggregated benefit received by the CPs is not guaranteed. We study two utility maximizing cooperative resource allocation games in a HDCF environment. We use price-based resource allocation strategy and present both centralized and distributed algorithms to find optimal solutions to these games. Various simulations were carried out to verify the proposed algorithms. The simulation results demonstrate that the algorithms are effective, showing robust performance for resource allocation and requiring minimal computation time.
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Amit, G., & Xia, C. H. (2011). Learning curves and stochastic models for pricing and provisioning cloud computing services. Service Science, 3, 99–109. CrossRef
An, B., Lesser, V., Irwin, D., & Zink, M. (2010). Automated negotiation with decommitment for dynamic resource allocation in cloud computing. In Proceedings of the 9th international conference on autonomous agents and multiagent systems, AAMAS ’10 (Vol. 1, pp. 981–988).
Andrade, N., Brasileiro, F., Cirne, W., & Mowbray, M. (2007). Automatic grid assembly by promoting collaboration in peer-to-peer grids. Journal of Parallel and Distributed Computating, 67, 957–966. CrossRef
Antoniadis, P., Fdida, S., Friedman, T., & Misra, V. (2010). Federation of virtualized infrastructures: Sharing the value of diversity. In Proceedings of the 6th international conference, Co-NEXT ’10 (pp. 12:1–12:12). New York: ACM.
Ardagna, D., Panicucci, B., & Passacantando, M. (2011). A game theoretic formulation of the service provisioning problem in cloud systems. In Proceedings of the 20th international conference on World Wide Web, WWW ’11 (pp. 177–186).
Assunção, M. D., Costanzo, A., & Buyya, R. (2010). A cost-benefit analysis of using cloud computing to extend the capacity of clusters. Cluster Computing, 13, 335–347. CrossRef
Auyoung, A., Chun, B., Snoeren, A., & Vahdat, A. (2004). Resource allocation in federated distributed computing infrastructures. In Proceedings of the 1st workshop on operating system and architectural support for the on-demand IT infrastructure. URL http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.2369.
Bittman, T. (2008). The evolution of the cloud computing market. Gartner Blog Network, http://blogs.gartner.com/thomasbittman/2008/11/03/theevolution-of-the-cloud-computing-market/.
Buyya, R., Ranjan, R., & Calheiros, R. (2010). Intercloud: Utility-oriented federation of cloud computing environments for scaling of application services. In Algorithms and architectures for parallel processing. Lecture notes in computer science (Vol. 6081, pp. 13–31).
Carroll, T. E., & Grosu, D. (2010). Formation of virtual organizations in grids: A game-theoretic approach. Concurrency and Computation: Practice and Experience, 22, 1972–1989. CrossRef
Celesti, A., Tusa, F., Villari, M., & Puliafito, A. (2010a). How to enhance cloud architectures to enable cross-federation. In IEEE international conference on cloud computing (pp. 337–345).
Celesti, A., Tusa, F., Villari, M., & Puliafito, A. (2010b). Three-phase cross-cloud federation model: The cloud sso authentication. In International conference on advances in future internet (pp. 94–101).
Cheng, W. K., Ooi, B. Y., & Chan, H. Y. (2010). Resource federation in grid using automated intelligent agent negotiation. Future Generations Computer Systems, 26, 1116–1126. CrossRef
Costanzo, A. d., Jin, C., Varela, C. A., & Buyya, R. (2009). Enabling computational steering with an asynchronous-iterative computation framework. In Proceedings of the 2009 fifth ieee international conference on e-Science, E-SCIENCE ’09 (pp. 255–262). Washington, D.C.: IEEE Computer Society. CrossRef
di Costanzo, A., de Assuncao, M. D., & Buyya, R. (2009). Harnessing cloud technologies for a virtualized distributed computing infrastructure. IEEE Internet Computing, 13, 24–33. CrossRef
Dodda, R. T., Smith, C., & Moorsel, A. (2009). An architecture for cross-cloud system management. In Contemporary computing. Communications in computer and information science (Vol. 40, pp. 556–567). Berlin: Springer.
Drew, F., & Jean, T. (1993). Game theory. Cambridge, MA: The MIT Press, ISBN-10: 0-262-06141-4
Elmroth, E., & Larsson, L. (2009). Interfaces for placement, migration, and monitoring of virtual machines in federated clouds. In GCC ’09: Proceedings of the 2009 eighth international conference on grid and cooperative computing (pp. 253–260).
Feldman, M., Lai, K., Stoica, I., & Chuang, J. (2004). Robust incentive techniques for peer-to-peer networks. In Proceedings of the 5th ACM conference on electronic commerce, EC ’04 (pp. 102–111)
Fontes, D. B. M. M., Hadjiconstantinou, E., & Christofides, N. (2006). A dynamic programming approach for solving single-source uncapacitated concave minimum cost network flow problems. European Journal of Operational Research, 174, 1205–1219. CrossRef
Fu, Y., Chase, J., Chun, B., Schwab, S., & Vahdat, A. (2003). Sharp: An architecture for secure resource peering. In Proceedings of the nineteenth ACM symposium on Operating systems principles (pp. 133–148). New York: ACM. CrossRef
Goiri, I., Guitart, J., & Torres, J. (2010). Characterizing cloud federation for enhancing providers’ profit. In IEEE international conference on cloud computing (pp. 123–130).
Gomes, E. R., Vo, Q. B., & Kowalczyk, R. (2010). Pure exchange markets for resource sharing in federated clouds. Concurrency and Computation: Practice and Experience. doi: 10.1002/cpe.1659.
He, L., & Ioerger, T. R. (2005). Forming resource-sharing coalitions: A distributed resource allocation mechanism for self-interested agents in computational grids. In Proceedings of the 2005 ACM symposium on applied computing, SAC ’05 (pp. 84–91).
Jalaparti, V., Nguyen, G. D., Gupta, I., & Caesar, M. (2010). Cloud resource allocation games. Technical Report, University of Illinois. http://hdl.handle.net/2142/17427.
Khan, S. U., & Ahmad, I. (2006). Non-cooperative, semi-cooperative, and cooperative games-based grid resource allocation. In Proceedings of the 20th international conference on parallel and distributed processing, IPDPS’06 (pp. 121–121).
Kolda, T. G., Lewis, R. M., & Torczon, V. (2003). Optimization by direct search: New perspectives on some classical and modern methods. SIAM Review, 45, 385–482. CrossRef
Kumar, C., Altinkemer, K., & De, P. (2011). A mechanism for pricing and resource allocation in peer-to-peer networks. Electronic Commerce Research and Applications, 10, 26–37. CrossRef
Lai, K., Rasmusson, L., Adar, E., Zhang, L., & Huberman, B. A. (2005). Tycoon: An implementation of a distributed, market-based resource allocation system. Multiagent and Grid Systems, 1, 169–182.
Lee, C., Suzuki, J., Vasilakos, A., Yamamoto, Y., & Oba, K. (2010). An evolutionary game theoretic approach to adaptive and stable application deployment in clouds. In Proceeding of the 2nd workshop on bio-inspired algorithms for distributed systems (pp. 29–38). New York: ACM. CrossRef
Li, M., Chen, M., & Xie, J. (2010). Cloud computing: A synthesis models for resource service management. In 2010 second international conference on communication systems, networks and applications (ICCSNA) (Vol. 2, pp. 208–211).
Ma, R., Lee, S., Lui, J., & Yau, D. (2006). Incentive and service differentiation in P2P networks: A game theoretic approach. IEEE/ACM Transactions on Networking, 14(5), 978–991. CrossRef
Macias, M., & Guitart, J. (2010). Using resource-level information into nonadditive negotiation models for cloud market environments. In 2010 IEEE network operations and management symposium (NOMS) (pp. 325–332).
Maximilien, E. M., Ranabahu, A., Engehausen, R., & Anderson, L. (2009). Ibm altocumulus: A cross-cloud middleware and platform. In OOPSLA ’09: Proceeding of the 24th ACM SIGPLAN conference companion on object oriented programming systems languages and applications (pp. 805–806).
OpenQRM (2010). The next generation, open-source data-center management platform. http://www.openqrm.com/.
Park, J., & van der Schaar, M. (2010). A game theoretic analysis of incentives in content production and sharing over peer-to-peer networks. IEEE Journal of Selected Topics in Signal Processing, 4(4), 704–717. CrossRef
Penmatsa, S., & Chronopoulos, A. T. (2011). Game-theoretic static load balancing for distributed systems. Journal of Parallel and Distributed Computing, 71, 537–555. CrossRef
Ranjan, R., & Buyya, R. (2008). Decentralized overlay for federation of enterprise clouds. CoRR abs/0811.2563.
Rochwerger, B., & Breitgand, D. (2009). The reservoir model and architecture for open federated cloud computing. IBM Journal of Research and Development, 53(4), 535–545. CrossRef
Subrata, R., & Zomaya, A. Y. (2008). Game-theoretic approach for load balancing in computational grids. IEEE Transactions on Parallel and Distributed Systems, 19, 66–76. CrossRef
Teng, F., & Magoulès, F. (2010). A new game theoretical resource allocation algorithm for cloud computing. In Advances in grid and pervasive computing. Lecture notes in computer science (Vol. 6104, pp. 321–330). Berlin: Springer.
Vicente, L. N. (2011). Worst case complexity of direct search. Department of Mathematics, University of Coimbra. http://www.mat.uc.pt/~lnv/papers/complex.pdf.
Wei, G., Vasilakos, V., Zheng, Y., & Xiong, N. (2010). A game-theoretic method of fair resource allocation for cloud computing services. Journal of Supercomputing, 54, 252–269. CrossRef
Wilkins, J., Ahmad, I., Fahad Sheikh, H., Faheem Khan, S., & Rajput, S. (2010). Optimizing performance and energy in computational grids using non-cooperative game theory. In Proceedings of the international conference on green computing, GREENCOMP ’10 (pp. 343–355).
Wolski, R., Brevik, J., Plank, J. S., & Bryan, T. (2003). Grid resource allocation and control using computational economies. In Grid computing: making the global infrastructure a reality (pp. 747–772). New York: Wiley. CrossRef
- Cooperative game-based distributed resource allocation in horizontal dynamic cloud federation platform
Mohammad Mehedi Hassan
M. Shamim Hossain
A. M. Jehad Sarkar
- Springer US
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