Abstract
The success of cloud computing paradigm has leveraged the emergence of a large number of new companies providing cloud computing services. This fact has been making difficult, for consumers, to choose which cloud providers will be the most suitable to attend their computing needs, satisfying their desired quality of service. To qualify such providers it is necessary to use metrics, such as performance indicators (PIs), useful for systematic and synthesized information collection. A genetic algorithm (GA) is a bio-inspired meta-heuristic tool used to solve various complex optimization problems. One of these complex optimization problems is to find the best set of cloud computing providers that satisfies a customer’s request, with the least amount of providers and the lowest cost. Thus, this article aims to model, apply and compare results of a GA and a deterministic matching algorithm for the selection of cloud computing providers.
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de Moraes, L.B., Fiorese, A., Parpinelli, R.S. (2018). An Evolutive Scoring Method for Cloud Computing Provider Selection Based on Performance Indicators. In: Castro, F., Miranda-Jiménez, S., González-Mendoza, M. (eds) Advances in Soft Computing. MICAI 2017. Lecture Notes in Computer Science(), vol 10632. Springer, Cham. https://doi.org/10.1007/978-3-030-02837-4_7
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