2011 IEEE International Conference on High Performance Computing and Communications 2011
DOI: 10.1109/hpcc.2011.111
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Dependability Modeling and Analysis for the Virtual Data Center of Cloud Computing

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Cited by 51 publications
(28 citation statements)
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“…SPNs provide a convenient way in this setting to represent energy flow and cooling in the infrastructure. Wei et al [69] proposes the use of GSPNs to evaluate the impact of virtualization mechanisms, such as VM consolidation and live migration, on cloud infrastructure dependability. GSPNs are used to provide fine-grained detail on the inner VM behaviors, such as separation of privileged and non-privileged instructions and successive handling by the VM or the VM monitor.…”
Section: Dependability Modelsmentioning
confidence: 99%
“…SPNs provide a convenient way in this setting to represent energy flow and cooling in the infrastructure. Wei et al [69] proposes the use of GSPNs to evaluate the impact of virtualization mechanisms, such as VM consolidation and live migration, on cloud infrastructure dependability. GSPNs are used to provide fine-grained detail on the inner VM behaviors, such as separation of privileged and non-privileged instructions and successive handling by the VM or the VM monitor.…”
Section: Dependability Modelsmentioning
confidence: 99%
“…In addition, state space models like Markov chains can be used for the modeling of more complicated interactions between components. Therefore, it seems that using hierarchical hybrid models [88], for example, combining RBDs and Generalized Stochastic Petri Nets (GSPNs) [89], RBDs and an MRM [90] are more suitable for evaluating cloud-based data centers' availability and reliability.…”
Section: "When Reliability and Ha Will Decrease In Cloud Computing Enmentioning
confidence: 99%
“…Wei [25] presents an hierarchical method to model and analyze virtual data center (VDC). The approach combines the advances of both RBD and General SPN (GSPN) for quantifying availability and reliability.…”
Section: Related Workmentioning
confidence: 99%