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arXiv · 2102.12222

Long-term IaaS Provider Selection using Short-term Trial Experience

Sheik Mohammad Mostakim Fattah·Athman Bouguettaya·Sajib Mistry
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Abstract

We propose a novel approach to select privacy-sensitive IaaS providers for a long-term period. The proposed approach leverages a consumer's short-term trial experiences for long-term selection. We design a novel equivalence partitioning based trial strategy to discover the temporal and unknown QoS performance variability of an IaaS provider. The consumer's long-term workloads are partitioned into multiple Virtual Machines in the short-term trial. We propose a performance fingerprint matching approach to ascertain the confidence of the consumer's trial experience. A trial experience transformation method is proposed to estimate the actual long-term performance of the provider. Experimental results with real-world datasets demonstrate the efficiency of the proposed approach.

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Sheik Mohammad Mostakim Fattah, Athman Bouguettaya, Sajib Mistry. 2021-02-24. Long-term IaaS Provider Selection using Short-term Trial Experience. https://doi.org/10.1109/icws.2019.00058

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