Determining Appropriate Large Object Stores with a Multi-criteria Approach

The area of storage solutions is becoming more and more heterogeneous. Even in the case of relational databases, there are several offerings, which differ from vendor to vendor and are offered for different deployments like on-premises or in the Cloud, as Platform-as-a-Service (PaaS) or as a special Virtual Machine on the Infrastructure-as-a-Service (IaaS) level. Beyond traditional relational databases, the NoSQL idea has gained a lot of attraction. Indeed, there are various services and products available from several providers. Each storage solution has virtues of its own even within the same product category for certain aspects. For example, some systems are offered as cloud services and pursue a pay-as-you-go principle without upfront investments or license costs. Others can be installed on premises, thus achieving higher privacy and security. Some store redundantly to achieve high reliability for higher costs. This paper suggests a multi-criteria approach for finding appropriate storage for large objects. Large objects might be, for instance, images of virtual machines, high resolution analysis images, or consumer videos. Multi-criteria means that individual storage requirements can be attached to objects and containers having the overall goal in mind to relieve applications from the burden to find corresponding appropriate storage systems. For efficient storage and retrieval, a metadata-based approach is presented that relies on an association with storage objects and containers. The heterogeneity of involved systems and their interfaces is handled by a federation approach that allows for transparent usage of several storages in parallel. All together applications benefit from the specific advantages of particular storage solutions for specific problems. In particular, the paper presents the required extensions for an object storage developed by the VISION Cloud project.