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Titlebook: Algorithmic Aspects of Cloud Computing; Third International Dan Alistarh,Alex Delis,George Pallis Conference proceedings 2018 Springer Int

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41#
發(fā)表于 2025-3-28 15:41:54 | 只看該作者
Exchange-Correlation Functionals,upports the decision-making of rule-based elasticity controllers to timely detect actual runtime changes in the monitorable load of cloud services. Results on real-life testbeds deployed on AWS, show that AdaFrame is able to correctly identify scaling actions and in contrast to the AWS auto-scaler, is able to lower detection delay by at least 63%.
42#
發(fā)表于 2025-3-28 21:52:49 | 只看該作者
Clusters and Cluster Reactions,nd develop a generalized mechanism to assign services to data centers based on the available resources in each data center and the distribution of the demand for each service. We further show, using simulations based on synthetic data that the scheme performs very well on different service workloads.
43#
發(fā)表于 2025-3-28 23:25:39 | 只看該作者
44#
發(fā)表于 2025-3-29 04:39:03 | 只看該作者
45#
發(fā)表于 2025-3-29 09:35:09 | 只看該作者
Improving Rule-Based Elasticity Control by Adapting the Sensitivity of the Auto-Scaling Decision Timupports the decision-making of rule-based elasticity controllers to timely detect actual runtime changes in the monitorable load of cloud services. Results on real-life testbeds deployed on AWS, show that AdaFrame is able to correctly identify scaling actions and in contrast to the AWS auto-scaler, is able to lower detection delay by at least 63%.
46#
發(fā)表于 2025-3-29 15:16:21 | 只看該作者
47#
發(fā)表于 2025-3-29 19:20:11 | 只看該作者
0302-9743 d Computing, ALGOCLOUD 2017, held in Vienna, Austria, in September 2017..The 9 revised full papers were carefully reviewed and selected from 27 submissions.?.The aim of the workshop is to present research activities and results on topics related to algorithmic, design, and development aspects of mod
48#
發(fā)表于 2025-3-29 23:12:12 | 只看該作者
Computing Probabilistic Queries in the Presence of Uncertainty via Probabilistic Automataelevant examples, where we show how to construct and exploit the convenient properties of such automata to evaluate RDF queries with adjustable cutoff. Finally, we present some directions for further investigation on this particular line of research, taking into account possible generalizations of this work.
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