Automated control in cloud computing: challenges and opportunities

By Harold Lim, Shivnath Babu, Jeffrey S. Chase, Sujay S. Parekh. Workshop on Automated Control for Datacenters and Clouds, 2009

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A Survey on Cloud Computing Elasticity (2012, methodology): “Replication is currently the most widely used method to provide elasticity, being used in most public providers [24] and in many works [18]–[22], [25], [27], [28].”
Empirical prediction models for adaptive resource provisioning in the cloud (2012, background): “Alternatively, Lim et al. [8] addressed the problem of building an effective external controller for automated adaptive scaling of applications deployed in the cloud.”
Elasticity in Cloud Computing: State of the Art and Research Challenges (2018, methodology): “[58], [60], [100], [101] use the adaptive utilization thresholds technique.”
Auto-scaling to minimize cost and meet application deadlines in cloud workflows (2011, background): “The first category is dynamic resource provisioning in virtualized environments (e.g., [4] [11]).”
Cloud auto-scaling with deadline and budget constraints (2010, background): “Further in [9], it focuses on control system design.”