<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "Modelling exogenous variability in cloud deployments"^^ . "Describing exogenous variability in the resources used by a cloud application leads to stochastic performance models that are difficult to solve. In this paper, we describe the blending algorithm, a novel approximation for queueing network models immersed in a random environment. Random environments are Markov chain-based descriptions of timevarying operational conditions that evolve independently of the system state, therefore they are natural descriptors for exogenous variability in a cloud deployment. The algorithm adopts the principle of solving a separate transient-analysis subproblem for each state of the random environment. Each subproblem is then approximated by a system of ordinary differential equations formulated according to a fluid limit theorem, making the approach scalable and computationally inexpensive. A validation study on several hundred models shows that blending can save up to two orders of magnitude of computational time compared to simulation, enabling efficient exploration of a decision space, which is useful in particular at design-time."^^ . "2013-03" . . "40" . "4" . . "ACM"^^ . . . "Performance Evaluation Review"^^ . . . "01635999" . . . . . . . . . . "Mirco"^^ . "Tribastone"^^ . "Mirco Tribastone"^^ . . "Giuliano"^^ . "Casale"^^ . "Giuliano Casale"^^ . . . . . "HTML Summary of #2604 \n\nModelling exogenous variability in cloud deployments\n\n" . "text/html" . . . "QA75 Electronic computers. Computer science"@en . .