Abstract
Cloud federation addresses the resource scalability issue by enabling infrastructure sharing among multiple clouds. We propose a proactive resource provisioning model for federation based on sliding window prediction technique. We compare the results of the proposed prediction mechanism with the commonly used time series prediction algorithm ARIMA. We developed a simulation environment for cloud federation to investigate the impact of workload prediction based resource provisioning in cloud federation. Finally we compare it with that of resource provisioning without prediction in a federated environment, evaluate the profit and resource utilization associated with both the cases.
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The research for this paper was financially supported by DST PURSE Phase II.
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Ramakrishnan, G., Anantharaman, P., Mukherjee, S. (2016). Proactive Resource Provisioning Model for Cloud Federation. In: Bjørner, N., Prasad, S., Parida, L. (eds) Distributed Computing and Internet Technology. ICDCIT 2016. Lecture Notes in Computer Science(), vol 9581. Springer, Cham. https://doi.org/10.1007/978-3-319-28034-9_22
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DOI: https://doi.org/10.1007/978-3-319-28034-9_22
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