Towards an Adaptive Middleware for Efficient Multi-Cloud Data Storage

Abstract

A multi-cloud storage architecture combines different storage technologies and resources from multiple clouds. As it allows application providers to manage the risks associated to technology or vendor lock-in, provider reliability, data security, privacy, it is an increasingly popular tactic for designing the storage tier of cloud-based applications. Multi-cloud storage architectures are however prone to run-time dynamicity: many dynamic properties impact the way such a setup is governed and evolved over time, e.g., storage providers enter or leave the market; pricing policies, QoS metrics and SLA guarantees change over time; etc. This paper provides an in-depth discussion of this complexity, and sketches our architectural vision of self-adaptive middleware solutions that monitor and change the storage architecture (semi-)autonomously. We highlight two areas of ongoing and future research that deserve specific attention: (i) systematically monitoring the storage systems, despite heterogeneity, and (ii) providing uniform methods and techniques to change and control the different storage resources dynamically.