Effective Modeling Approach for IaaS Data Center Performance Analysis under Heterogeneous Workload

Abstract

Heterogeneity prevails not only among physical machines but also among workloads in real IaaS Cloud data centers (CDCs). The heterogeneity makes performance modeling of large and complex IaaS CDCs even more challenging. This paper considers the scenario where the number of virtual CPUs requested by each customer job may be different. We propose a hierarchical stochastic modeling approach applicable to IaaS CDC performance analysis under such a heterogeneous workload. Numerical results obtained from the proposed analytic model are verified through discrete-event simulations under various system parameter settings.