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Aggregated Rank in First-Fit-Decreasing for Green Cloud Computing

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Cognitive Informatics and Soft Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 768))

Abstract

Virtual Machine (VM) placement in a cloud data center is a Vector Bin-Packing (VBP) problem to minimize the number of PMs used for hosting the given VM requests. First-Fit-Decreasing (FFD) variants are widely used for VM placement. In this paper, a novel FFD variant, Aggregated Rank in FFD (FFD-AR) is proposed for VM placement. Simulation experiments were carried out using two datasets: a dataset inspired by Amazon EC2 instances and another is a synthetic dataset. The packing efficiency of the proposed FFD-AR results is better as compared to all the other baseline FFD variants. We believe the proposed FFD-AR can be applied to wide applications of VBP like production planning and logistics.

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Acknowledgements

The authors thank the Department of Science and Technology for their financial support (SR/FST/ETI-349/2013) under Fund for Improvement of S&T Infrastructure in Universities and Higher Educational Institutions.

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Correspondence to Saikishor Jangiti .

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Jangiti, S., Sri Ram, E., Shankar Sriram, V.S. (2019). Aggregated Rank in First-Fit-Decreasing for Green Cloud Computing. In: Mallick, P., Balas, V., Bhoi, A., Zobaa, A. (eds) Cognitive Informatics and Soft Computing. Advances in Intelligent Systems and Computing, vol 768. Springer, Singapore. https://doi.org/10.1007/978-981-13-0617-4_53

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