In enterprise data centers power usage is a problem impacting server density and the total cost of ownership. Storage uses a significant fraction of the power budget and there are no widely deployed power-saving solutions for enterprise storage systems. The traditional view is that enterprise workloads make spinning disks down ineffective because idle periods are too short. We analyzed block-level traces from 36 volumes in an enterprise data center for one week and concluded that significant idle periods exist, and that they can be further increased by modifying the read/write patterns using write off-loading. Write off-loading allows write requests on spun-down disks to be temporarily redirected to persistent storage elsewhere in the data center. The key challenge is doing this transparently and efficiently at the block level, without sacrificing consistency or failure resilience. We describe our write offloading design and implementation that achieves these goals. We evaluate it by replaying portions of our traces on a rack-based testbed. Results show that just spinning disks down when idle saves 28–36 % of energy, and write off-loading further increases the savings to 45–60%. 1

As the world moves to digital storage for archival purposes, there is an increasing demand for reliable, lowpower, cost-effective, easy-to-maintain storage that can still provide adequate performance for information retrieval and auditing purposes. Unfortunately, no current archival system adequately fulfills all of these requirements. Tape-based archival systems suffer from poor random access performance, which prevents the use of inter-media redundancy techniques and auditing, and requires the preservation of legacy hardware. Many diskbased systems are ill-suited for long-term storage because their high energy demands and management requirements make them cost-ineffective for archival purposes. Our solution, Pergamum, is a distributed network of intelligent, disk-based, storage appliances that stores data reliably and energy-efficiently. While existing MAID systems keep disks idle to save energy, Pergamum adds NVRAM at each node to store data signatures, metadata, and other small items, allowing deferred writes, metadata requests and inter-disk data verification to be performed while the disk is powered off. Pergamum uses both intra-disk and inter-disk redundancy to guard against data loss, relying on hash tree-like structures of algebraic signatures to efficiently verify the correctness of stored data. If failures occur, Pergamum uses staggered rebuild to reduce peak energy usage while rebuilding large redundancy stripes. We show that our approach is comparable in both startup and ongoing costs to other archival technologies and provides very high reliability. An evaluation of our implementation of Pergamum shows that it provides adequate performance. 1

Hard disks contain data—frequently an irreplaceable asset of high monetary and non-monetary value. At the same time, hard disks are mechanical devices that consume power, are noisy, and fragile when their platters are rotating. In this paper we demonstrate that hard disks cause different kinds of problems for different types of computer systems and demystify several common misconceptions. We show that solutions developed to date are incapable of solving the power consumption, noise, and data reliability problems without sacrificing hard disk life-time, data reliability, or user convenience. We considered data reliability, recovery, performance, user convenience, and hard disk-caused problems together at the enterprise scale. We have designed GreenFS: a fan-out stackable file system that offers all-time all-data run-time data protection, improves performance under typical user workloads, and allows hard disks to be kept off most of the time. As a result, GreenFS improves enterprise data protection, minimizes disk drive-related power consumption and noise and increases the chances of disk drive survivability in case of unexpected external impacts.

Multi-tier systems that combine SSDs with SAS/FC and/or SATA disks mitigate the capital cost burden of SSDs, while benefiting from their superior I/O performance per unit cost and low power. Though commercial SSD-based multi-tier solutions are available, configuring such a system with the optimal number of devices per tier to achieve performance goals at minimum cost remains a challenge. Furthermore, these solutions do not leverage the opportunity to dynamically consolidate load and reduce power/operating cost. Our extent-based dynamic tiering solution, EDT, addresses these limitations via two key components of its design. A Configuration Adviser EDT-CA determines the adequate mix of storage devices to buy and install to satisfy a given workload at minimum cost, and a Dynamic Tier Manager EDT-DTM performs dynamic extent placement once the system is running to satisfy performance requirements while minimizing dynamic power consumption. Key to the cost minimization of EDT-CA is its ability to simulate the dynamic extent placement afforded by EDT-DTM. Key to the overall effectiveness of EDT-DTM is its ability to consolidate load within tiers when feasible, rapidly respond to unexpected changes in the workload, and carefully control the overhead due to extent migration. Our results using production workloads show that EDT incurs lower capital and operating cost, consumes less power, and delivers similar or better performance relative to SAS-only storage systems as well as other simpler approaches to extent-based tiering. 1

We consider large scale, distributed storage systems with a redundancy mechanism; cloud storage being a prime example. We investigate how such systems can reduce their power consumption during low-utilization time intervals by operating in a low-power mode. In a low power mode, a subset of the disks or nodes are powered down, yet we ask that each data item remains accessible in the system; this is called full coverage. The objective is to incorporate this option into an existing system rather than redesign the system. When doing so, it is crucial that the low power option should not affect the performance or other important characteristics of the system during full-power (normal) operation. This work is a comprehensive study of what can or cannot be achieved with respect to full coverage low power modes. The paper addresses this question for generic distributed storage systems (where the key component under investigation is the placement function of the system) as well as for specific popular system designs in the realm of storing data in the cloud. Our observations and techniques are instrumental for a wide spectrum of systems, ranging from distributed storage systems for the enterprise to cloud data services. In the cloud environment where low cost is imperative, the effects of such savings are magnified by the large scale.

Abstract—Archival storage systems designed to preserve scientific data, business data, and consumer data must maintain and safeguard tens to hundreds of petabytes of data on tens of thousands of media for decades. Such systems are currently designed in the same way as higherperformance, shorter-term storage systems, which have a useful lifetime but must be replaced in their entirety via a “fork-lift ” upgrade. Thus, while existing solutions can provide good energy efficiency and relatively low cost, they do not adapt well to continuous improvements in technology, becoming less efficient relative to current technology as they age. In an archival storage environment, this paradigm implies an endless series of wholesale migrations and upgrades to remain efficient and up to date. Our approach, Logan, manages node addition, removal, and failure on a distributed network of intelligent storage appliances, allowing the system to gradually evolve as device technology advances. By automatically handling most of the common administration chores—integrating new devices into the system, managing groups of devices that work together to provide redundancy, and recovering from failed devices—Logan reduces management overhead and thus cost. Logan can also improve cost and space efficiency by identifying and decommissioning outdated devices, thus reducing space and power requirements for the archival storage system. I.

Energy consumption for computing devices in general and for data centers in particular is receiving increasingly high attention, both because of the increasing ubiquity of computing and also because of increasing energy prices. In this work, we propose QMD (Quasi Mirrored Disks) that exploit flash as a write buffer to complement RAID systems consisting of hard disks. QMD along with partial on-line mirrors, are a first step towards energy proportionality which is seen as the "holy grail " of energy-efficient system design. QMD exhibits significant energy savings of up 31%, as per our evaluation study using real workloads. 1.