Signature-based Selection of IaaS Cloud Services
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Abstract (arXiv)
We propose a novel approach to select IaaS cloud services for a long-term period where the service providers offer limited QoS information. The proposed approach leverages free short-term trials to obtain the previously undisclosed QoS information. A new significance-based trial scheme is proposed using frequency distribution analysis to test a consumer's long-term workloads in a short trial. We introduce a novel IaaS signature technique to uniquely identify the variability of a provider's QoS performance. A Signature-based QoS Performance Discovery (SPD) algorithm is proposed which leverages the combination of free trials and IaaS signatures. A set of exhaustive experiments with real-world datasets is conducted to evaluate the proposed approach.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 26 Apr 2020.
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- 2021Sequential Learning-based IaaS Compositioncited by 0
- 2021Sequential Learning-based IaaS Composition24 Feb 2021