Performability Analysis for IaaS Cloud Data Center

Abstract

Cloud computing has been bringing fundamental changes to computing models in the past few years. Infrastructure as a Service (IaaS), a kind of basic cloud services, is provisioned to customers in the form of virtual machines (VMs). The increasing demands for IaaS cloud services require the performability analysis of cloud infrastructure. Analytic modeling is one of the effective evaluation approaches. This paper aims to develop a monolithic model, by using continuous time Markov chain (CTMC), for a IaaS CDC, which (1) consists of active and standby physical machines (PMs), (2) allows PM migration among active and standby PM pools, (3) all jobs are homogeneous, and (4) a running job could continue its running by using idle active PMs when the PM working for this job fails. Although a monolithic CTMC model for IaaS Cloud performability analysis may face largeness and stiffness problems, it could be used to verify the scalable approximate model. We present the details of state transition rules of the proposed model and the formula for computing metrics, including the immediate service probability, the mean response time and so on. Numerical analysis and simulations are carried out to verify the accuracy of the proposed model.