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Distributed Resource Allocation Approach on Federated Clouds

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Frontier Computing (FC 2016)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 422))

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Abstract

This paper addresses the distributed resource allocation problem in the federated cloud environment, in which the deployment and management of multiple clouds aim to meet the clients’ requirement. In such an environment, users could optimize service delivery by selecting the most suitable provider, in terms of cost, efficiency, flexibility, and availability of services, to deploy applications. However, different providers have different resource allocation strategies. This paper proposes a distributed resource allocation approach to solve resource competition in the federated cloud environment. Experimental results show that the cloud provider could obtain more profits by outsourcing resources in the federated cloud with enough resources.

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References

  1. Mell, P., and Grance, T., The NIST Definition of Cloud Computing. NIST Special Publication 800–145, 2011.

    Google Scholar 

  2. Moreno-Vozmediano, R., Montero, R.S., Llorente, I. M., “IaaS Cloud Architecture: From Virtualized Datacenters to Federated Cloud Infrastructures,” IEEE Computer, Vol. 45, No. 12, 65– 72, 2012.

    Google Scholar 

  3. Calheiros, R. N., Toosi, A. N., Vecchiola, C., Buyya, R., “A Coordinator for Scaling Elastic Applications across Multiple Clouds,” Future Generation Computer Systems, Vol. 28, No. 8, 2012, pp. 1350–1362.

    Google Scholar 

  4. Sedaghat, M., Hernandez-Rodriguez, F., Elmroth, E., “A virtual machine re-packing approach to the horizontal vs. vertical elasticity trade-off for cloud autoscaling,” Proceedings of the 2013 ACM Cloud and Autonomic Computing, Article No. 6, 2013.

    Google Scholar 

  5. Hussain, H., et al., “A survey on resource allocation in high performance distributed computing systems,” Parallel Computing, Vol. 39, No. 11, pp. 709–736, 2013.

    Google Scholar 

  6. Wei, X., Li, H., Yang, K., Zou, L., “Topology-aware Partial Virtual Cluster Mapping Algorithm on Shared Distributed Infrastructures,” IEEE Transactions on Parallel and Distributed Systems, Vol. 25, No. 10, pp. 2721–2730, 2014.

    Google Scholar 

  7. Palmieri, F., Buonanno, L., Venticinque, S., Aversa, R. and Martino, B.D., “A distributed scheduling framework based on selfish autonomous agents for federated cloud environments,” Future Generation Computer Systems, Vol. 29, No. 6, pp. 1461–1472, 2013.

    Google Scholar 

  8. Ye, D. and Chen, J., “Non-cooperative games on multidimensional resource allocation,” Future Generation Computer Systems, Vol. 29, No. 6, 2013, pp. 1345–1352.

    Google Scholar 

  9. Hassan, M., Song, B. and Huh, E.N., “Game-based distributed resource allocation in horizontal dynamic cloud federation platform,” in Algorithms and Architectures for Parallel Processing, Y. Xiang, A. Cuzzocrea, M. Hobbs, and W. Zhou, Eds., Vol. 7016 of Lecture Notes in Computer Science, pp. 194–205, Springer, 2011.

    Google Scholar 

  10. Wooldridge, M., “Does Game Theory Work?” IEEE Intelligent Systems, pp. 76–80, November, 2012.

    Google Scholar 

  11. Mao, Z., Yang, J., Shang, Y., Liu, C. and Chen, J., “A game theory of cloud service deployment,” 2013 IEEE World Congress on Services (SERVICES), pp. 436–443, June 2013.

    Google Scholar 

  12. Sullivan, A., Sheffrin S.M., Economics: Principles in action. Upper Saddle River, New Jersey 07458: Pearson Prentice Hall. 2003.

    Google Scholar 

  13. Trent, R.J. and Monczka, R.M., “Cost-Driven Pricing: An Innovative Approach for Managing Supply Chain Costs,” Supply Chain Forum: an International Journal, Vol. 4, No. 1, pp. 2–10, 2003.

    Google Scholar 

  14. Maui, http://docs.adaptivecomputing.com/maui/.

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Acknowledgements

This study was sponsored by the Ministry of Science and Technology, Taiwan, R.O.C., under contract numbers: MOST 103-2218-E-007-021 and MOST 103-2221-E-142-001-MY3.

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Correspondence to Kuan-Chou Lai .

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Lee, YH., Huang, KC., Shieh, MR., Lai, KC. (2018). Distributed Resource Allocation Approach on Federated Clouds. In: Yen, N., Hung, J. (eds) Frontier Computing. FC 2016. Lecture Notes in Electrical Engineering, vol 422. Springer, Singapore. https://doi.org/10.1007/978-981-10-3187-8_27

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  • DOI: https://doi.org/10.1007/978-981-10-3187-8_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3186-1

  • Online ISBN: 978-981-10-3187-8

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