Feature-Model-Based Commonality and Variability Analysis for Virtual Cluster Disk Provisioning

摘要

The rapid growth of networking and storage capacity allows collecting and analyzing massiveamount of data by relying increasingly on scalable, flexible, and on-demand provisioned largescalecomputing resources. Virtualization is one of the feasible solution to provide largeamounts of computational power with dynamic provisioning of underlying computing resources.Typically, distributed scientific applications for analyzing data run on cluster nodes to performthe same task in parallel. However, on-demand virtual disk provisioning for a set of virtualmachines, called virtual cluster, is not a trivial task. This paper presents a feature model-basedcommonality and variability analysis system for virtual cluster disk provisioning to categorizetypes of virtual disks that should be provisioned. Also, we present an applicable case study toanalyze common and variant software features between two different subgroups of the big dataprocessing virtual cluster. Consequently, by using the analysis system, it is possible to providean ability to accelerate the virtual disk creation process by reducing duplicate softwareinstallation activities on a set of virtual disks that need to be provisioned in the same virtualcluster.