Investigate Data Center Performance and QOS in IAAS Cloud Computing Systems Using a Stochastic Model
Cloud data center management is a key problem due to the numerous and heterogeneous strategies that can be applied, ranging from the VM (Virtual Machine) placement to the federation with other clouds. Performance evaluation of cloud computing infrastructures is required to predict and quantify the cost-benefit of a strategy portfolio and the corresponding Quality of Service (QoS) experienced by users. Such analyses are not feasible by simulation or on the field experimentation, due to the great number of parameters that have to be investigated. In this paper, the authors present an analytical model, based on Stochastic Reward Nets (SRNs), that is both scalable to model systems composed of thousands of resources and flexible to represent different policies and cloud-specific strategies.
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