A SVM-based Multi-dimension Factor Decision-making Model Framework

Abstract

The cloud-desktop based on the virtual desktop infrastructure (VDI) is deployed more often as the advanced mobile office solution. However, it is an assignable challenge to choose a fit VDI product at low cost for too many testing features to be investigated. In this paper, we proposed a SVM-based multi-dimension factor decision-making model framework (SMFDMF) for the VDI-based cloud-desktop application evaluation. SMFDMF is highly data adaptive, applies and is able to account for correlation as well as interactions among features. This makes SMFDMF particularly appealing for high-dimensional cloud-desktop testing feature analysis. The experiment results show that our SMFDMF is workable, easy to implement and result in good estimation accuracies.