Cooperative Storage-Level De-Duplication for I/O Reduction in Virtualized Data Centers

Min Li, Shravan Gaonkar, Ali R. Butt, Deepak Kenchammana, and Kaladhar Voruganti.

This paper explores the synergy between the two layers of storage and server virtualization to exploit block sharing information.

Data centers are increasingly being re-designed for workload consolidation in order to reap the benefits of better resource utilization, power savings, and physical space savings. Among the forces driving savings are server and storage virtualization technologies. As more consolidated workloads are concentrated on physical machines—e.g., the virtual density is already very high in virtual desktop environments, and will be driven to unprecedented levels with the fast growing high-core counts of physical servers—the shared storage layer must respond with virtualization innovations of its own such as de-duplication and thin provisioning. A key insight of this paper is that there is a greater synergy between the two layers of storage and server virtualization to exploit block sharing information than was previously thought possible. We reveal this via developing a systematic framework to explore the storage and virtualization servers interactions.We also quantitatively evaluate the I/O bandwidth and latency reduction that is possible between virtual machine hosts and storage servers using real-world trace driven simulation. Moreover, we present a proof of concept NFS implementation that incorporates our techniques to quantify their I/O latency benefits.

In Proceedings of the IEEE 20th International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication Systems 2012 (MASCOTS ’12)

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IO-Reduction-mascots2012.pdf