Tag Archives: ieee

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)

Resources

  • The author’s version of the paper is attached to this posting. Please observe the following copyright:

© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

IO-Reduction-mascots2012.pdf

SLO-aware Hybrid Store

msst-whitebg.pngPriya Sehgal, Kaladhar Voruganti, and Rajesh Sundaram.

In this paper we present an SLO based resource management algorithm that controls the amount of SSD given to a particular workload.

In the past storage vendors used different types of storage depending upon the type of workload. For example, they used Solid State Drives (SSDs) or FC hard disks (HDD) for online transaction, while SATA for archival type workloads. However, recently many storage vendors are designing hybrid SSD/HDD based systems that can satisfy multiple service level objectives (SLOs) of different workloads all placed together in one storage box, at better cost points. The combination is achieved by using SSDs as a read-write cache while HDD as a permanent store. In this paper we present an SLO based resource management algorithm that controls the amount of SSD given to a particular workload. This algorithm solves following problems: 1) it ensures that workloads do not interfere with each other 2) it ensure that we do not overprovision (cost wise) the amount of SSD allocated to a workload to satisfy its SLO (latency requirement) and 3) dynamically adjust SSD allocated in light of changing workload characteristics (i.e., provide only required amount of SSD). We have implemented our algorithm in a prototype Hybrid Store, and have tested its efficacy using many real workloads. Our algorithm satisfies latency SLOs almost always by utilizing close to optimal amount of SSD and saving 6-50% of SSD space compared to the naïve algorithm

In Proceedings of the IEEE Conference on Mass Storage Systems and Technologies 2012 (MSST’12)

Resources

  • The author’s version of the paper is attached to this posting, please observe the following copyright:

© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

 
msst-SLOAware.pdf