Abstract
Resource management in cloud environment poses unique challenges. Resources, in the form of virtual machines (VM) are to be provisioned on the fly while using the underlying infrastructure efficiently and still meeting the performance parameters. This involves collecting system resource statistics for decision making by other components of cloud environment. In this paper, the process of resource (VM) management in the cloud is mapped to demand based system wherein the VMs that require additional resources or need to relinquish their resources send requests to a centralized controller. Further, since resources are limited, dynamic resource allocation forms a classical optimization problem. This paper proposes a one-dimensional knapsack optimization solved using dynamic programming, to achieve efficient resource allocation. The performance of the proposed algorithm has been compared with brute force algorithm.
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References
Mell, P., Grance, T.: Perspectives on cloud computing and standards. Technical report, National Institute of Standards and Technology (NIST), Information Technology Laboratory (2009)
Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J., Brandic, I.: Cloud computing and emerging it platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Generation Computer Systems 25(6), 599–616 (2009)
Tierney, B., Aydt, R., Gunter, D., Smith, W., Swany, M., Taylor, V., Wolski, R.: A grid monitoring architecture. The Global Grid Forum Draft Recommendation, GWD-Perf-16-3 (2002)
Cooke, A., Gray, A., Nutt, W., Magowan, J., Oevers, M., Taylor, P.: The relational grid monitoring architecture: Mediating information about the grid. Journal of Grid Computing, 323–339 (2004)
Brandt, J., Gentile, A., Mayo, J., Pebay, P., Roe, D., Thompson, D., Wong, M.: Resource monitoring and management with ovis to enable hpc in cloud computing environments. In: Proceedings of the 2009 IEEE International Symposium on Parallel & Distributed Processing, IPDPS 2009, pp. 1–8. IEEE Computer Society, Washington, DC (2009)
Yazir, Y., Matthews, C., Farahbod, R., Neville, S., Guitouni, A., Ganti, S., Coady, Y.: Dynamic resource allocation based on distributed multiple criteria decisions in computing cloud. In: 3rd International Conference on Cloud Computing, pp. 91–98 (2010)
Nurmi, D., Wolski, R., Grzegorczyk, C., Obertelli, G., Soman, S., Youseff, L., Zagorodnov, D.: The eucalyptus open-source cloud-computing system. In: 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, CCGRID 2009, pp. 124–131. IEEE (2009)
Kavanagh, D.: Typica: A java client library for a variety of amazon web services (2008), https://code.google.com/p/typica/
Arlitt, M.F., Williamson, C.L.: Internet web servers: Workload characterization and performance implications. IEEE/ACM Transactions on Networking (ToN) 5(5), 631–645 (1997)
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Sahu, S., Gupta, H., Singh, S., Ghosh, S.K. (2014). A Demand Based Resource Provisioner for Cloud Infrastructure. In: Kumar Kundu, M., Mohapatra, D., Konar, A., Chakraborty, A. (eds) Advanced Computing, Networking and Informatics- Volume 2. Smart Innovation, Systems and Technologies, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-07350-7_47
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DOI: https://doi.org/10.1007/978-3-319-07350-7_47
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07349-1
Online ISBN: 978-3-319-07350-7
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