Analytical modeling of performance indices under epistemic uncertainty applied to cloud computing systems

• Published in: Future generation computer systems Vol. 102; pp. 746 - 761
• Main Authors: Antonelli, Fabio, Cortellessa, Vittorio, Gribaudo, Marco, Pinciroli, Riccardo, Trivedi, Kishor S., Trubiani, Catia
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.01.2020
• Subjects: Cloud computing; CloudSim; Confidence interval; Epistemic uncertainty propagation; M/M/1 queue; Performance modeling; Uncertainty modeling; VM migration; Cloud computing; M/M/1 queue; Uncertainty modeling; Performance modeling; CloudSim; VM migration; Epistemic uncertainty propagation; Confidence interval

The extent of epistemic uncertainty in modeling and analysis of complex systems is ever growing, mainly due to increasing levels of the openness, heterogeneity and versatility in cloud-based applications that are being adopted in critical sectors, like banking and finance. State-of-the-art approache...