Cloud Computing: Survey on Energy Efficiency <s> Storage Systems. <s> High energy consumption has become a critical challenge in all kinds of computer systems. Hardware-supported Dynamic Power Management (DPM) provides a mechanism to save disk energy by transitioning an idle disk to a low-power mode. However, the achievable disk energy saving is mainly dependent on the pattern of I/O requests received at the disk. In particular, for a given number of requests, a bursty disk access pattern serves as a foundation for energy optimization. Aggressive prefetching has been used to increase disk access burstiness and extend disk idle intervals, while caching, a critical component in buffer cache management, has not been paid a specific attention. In the absence of cooperation from caching, the attempt to create bursty disk accesses would often be disturbed due to improper replacement decision made by energy unaware caching policies. In this paper, we present the design of a set of comprehensive energy-aware caching schemes, called C-Burst, and its implementation in Linux kernel 2.6.21. Our caching schemes leverage the 'filtering' effect of buffer cache to effectively reshape the disk access stream to a bursty pattern for energy saving. The experiments under various scenarios show that C-Burst schemes can achieve up to 35% disk energy saving with minimal performance loss. <s> BIB001 </s> Cloud Computing: Survey on Energy Efficiency <s> Storage Systems. <s> Large-scale parallel disk systems are frequently used to meet the demands of information systems requiring high storage capacities. A critical problem with these large-scale parallel disk systems is the fact that disks consume a significant amount of energy. To design economically attractive and environmentally friendly parallel disk systems, we developed two energy-aware prefetching strategies for parallel disk systems with disk buffers. First, we introduce a new buffer disk architecture that can provide significant energy savings for parallel disk systems while achieving high performance. Second, we design a prefetching approach to utilize an extra disk to accommodate prefetched data sets that are frequently accessed. Third, we develop a second prefetching strategy that makes use of an existing disk in the parallel disk system as a buffer disk. Compared with the first prefetching scheme, the second approach lowers the capacity of the parallel disk system. However, the second approach is more cost-effective and energy-efficient than the first prefetching technique. Finally, we quantitatively compare both of our prefetching approaches against two conventional strategies including a dynamic power management technique and a non-energy-aware scheme. Using empirical results we show that our novel prefetching approaches are able to reduce energy dissipation in parallel disk systems by 44% and 50% when compared against a non-energy aware approach. Similarly, our strategies are capable of conserving 22% and 30% of the energy when compared to the dynamic power management technique. <s> BIB002 </s> Cloud Computing: Survey on Energy Efficiency <s> Storage Systems. <s> Today's storage systems place an imperative demand on energy efficiency. A storage system often places single-rotation- rate disks into standby mode by stopping them from spinning to conserve energy when the workload is not heavy. The major obstacle of this method is a high spin-up cost introduced by passively waking up the standby disk to service requests. In this paper, we propose a redundancy-based hierarchical I/O cache architecture called RIMAC to solve the problem. The idea of RIMAC is to enable data on the standby disk(s) to be recovered by accessing a two-level I/O cache and/or active disks if needed. In parity-based redundant disk arrays, RIMAC exploits parity redundancy to dynamically XOR-reconstruct the data being accessed toward standby disk(s) at both the cache and disk levels. By avoiding passive spin-ups, RIMAC can significantly improve both energy efficiency and performance. In RIMAC, we developed 1) two power-aware read request transformation schemes called Transformable Read in Cache (TRC) and Transformable Read on Disk (TRD), 2) a power-aware write request transformation policy for parity update, and 3) a second-chance parity cache replacement algorithm to favor the request transformation rate. We evaluated RIMAC by augmenting a validated storage system simulator, DiskSim, and tested three real-life server traces, including HP's cello99, UlUC's OLTP, and SPC's search engine. Comprehensive results indicate that RIMAC is able to reduce energy consumption by up to 18 percent and simultaneously improve the average response time by up to 34 percent compared with threshold-based power management schemes for single-rotation-rate disk- based RAIDs. <s> BIB003 </s> Cloud Computing: Survey on Energy Efficiency <s> Storage Systems. <s> In this paper, we propose a static cache management policy for RAID architecture which uses an SSD as a disk cache. Because SSD has several drawbacks, dynamic cache management scheme such as LRU can cause serious problem i.e., too much write operations can be occurred in order to contain most recently used data. Frequent write operations on SSD not only slow down the performance but also shorten the lifetime. For this reason, we propose a static cache management policy which takes popularity and size into account. Popular data of some period is copied into SSD and too large files are excluded since too large files can lower the hit ratio. We used real trace to evaluate our scheme and the results showed that write counts are reduced to 1/37 of LRU policy as we desired. Unfortunately, the average hit ratio was lower than LRU policy but when popular data is similar between two periods, our scheme showed better hit ratio than LRU. This implies that our scheme can be used on web server which follows zipf’s distribution and has smooth changing of popular data. <s> BIB004 </s> Cloud Computing: Survey on Energy Efficiency <s> Storage Systems. <s> Cluster storage systems are essential building blocks for many high-end computing infrastructures. Although energy conservation techniques have been intensively studied in the context of clusters and disk arrays, improving energy efficiency of cluster storage systems remains an open issue. To address this problem, we describe in this paper an approach to implementing an energy-efficient cluster storage system or ECOS for short. ECOS relies on the architecture of cluster storage systems in which each I/O node manages multiple disks - one buffer disk and several data disks. Given an I/O node, the key idea behind ECOS is to redirect disk requests from data disks to the buffer disk. To balance I/O load among I/O nodes, ECOS might redirect requests from one I/O node into the others. Redirecting requests is a driving force of energy saving, and the reason is two-fold. First, ECOS makes an effort to keep buffer disks active while placing data disks into standby in a long time period to conserve energy. Second, ECOS reduces the number of disk spin downs/ups in I/O nodes. The idea of ECOS was implemented in a Linux cluster, where each I/O node contains one buffer disk and two data disks. Experimental results show that ECOS improves the energy efficiency of traditional cluster storage systems where buffer disks are not employed. Adding one extra buffer disk into each I/O node seemingly has negative impact on energy saving. Interestingly, our results indicate that ECOS equipped with extra buffer disks is more energy efficient than the same cluster storage system without the buffer disks. The implication of the experiments is that using existing data disks in I/O nodes to perform as buffer disks can achieve even higher energy efficiency. <s> BIB005 </s> Cloud Computing: Survey on Energy Efficiency <s> Storage Systems. <s> In the past decade parallel disk systems have been highly scalable and able to alleviate the problem of disk I/O bottleneck, thereby being widely used to support a wide range of data-intensive applications. Optimizing energy consumption in parallel disk systems has strong impacts on the cost of backup power-generation and cooling equipment, because a significant fraction of the operation cost of data centres is incurred by energy consumption and cooling. Although flash memory is very energy- efficient compared to disk drives, flash memory is too expensive to use as a major component in large-scale storage systems. In other words, it is not a cost-effective way to make use of large flash memory to build energy-efficient storage systems. To address this problem, in this paper we proposed a hybrid disk architecture or HYBUD that integrates a non-volatile flash memory with buffer disks to build cost-effective and energy-efficient parallel disk systems. While the most popular data sets are cached in flash memory, the second most popular data sets can be stored and retrieved from buffer disks. HYBUD is energy efficient because flash memory coupled with buffer disks can serve a majority of incoming disk requests, thereby keeping a large number of other data disks in the low-power state for longer period times. Furthermore, HYBUD is cost-effective by the virtue of inexpensive buffer disks assisting flash memory to cache a huge amount of popular data. Experimental results demonstratively show that compared with two existing non-hybrid architectures, HYBUD provides significant energy savings for parallel disk systems in a very cost effective way. Keywords-hybrid parallel disk systems; flash drives; buffer disks; energy conservation; I/O performance <s> BIB006 </s> Cloud Computing: Survey on Energy Efficiency <s> Storage Systems. <s> The HDD industry is at a critical technology cross roads and it is paramount that we quickly establish comprehensive paths to push beyond the superparamagnetic limit. Several promising technology options have been explored to increase the areal density beyond the limit such as bit patterned magnetic recording (BPMR), heat assisted magnetic recording (HAMR), and microwave assisted magnetic recording (MAMR). In addition to these three technology options, there is recent interest in a fourth approach that has the advantage of staying with a relatively conventional perpendicular medium and head. This combines shingled write recording (SWR) and/or 2-D read back and signal processing. Either technique can be used separately to give large gains and the combination of the two, which is referred to as 2-D magnetic recording (TDMR), promises particularly large gains. Recording with energy assist on BPM or 2-D signal processing will enable the areal density beyond around 5 Tb/in2, although none of them have shown a clear problem-free solution. Precompetitive research projects and programs have recently started targeting 2 Tb/in2 by 2010 for SRC, 5 Tb/in2 by 2013 for NEDO, and 10 Tb/in2 by 2015 for INSIC. This paper reviews the technology options ahead, and the pros & cons for each option. We include a brief introduction to SWR and TDMR. <s> BIB007 </s> Cloud Computing: Survey on Energy Efficiency <s> Storage Systems. <s> Modern disk-based storage systems are not energy proportional, because disks consume almost as much power when idle (but spinning) as they do when actively accessing data. We combine a power-aware, solid-state (flash) cache and a reliability-aware disk spindown mechanism to significantly improve storage energy proportionality without hurting disk reliability, data integrity, or performance. We evaluated the resulting power- and reliability-aware hybrid flash-disk RAID storage array and found that it reduces energy consumption by 85% compared to a similar-cost, similar-performance typical configuration of all SAS drives that are never spun down. Our design also achieves almost 50% energy savings compared to hybrid flash-disk systems tuned for performance or that do not take full advantage of opportunities for safe spindown. Further, unlike most previous work that exploits spindown to save energy, we limit the rate at which disks are spun down to avoid premature mechanical failures, whereas reliability-unaware spindown algorithms can exceed manufacturer waranteed lifetime spindown limits in as little as one year. <s> BIB008 </s> Cloud Computing: Survey on Energy Efficiency <s> Storage Systems. <s> Much research has been conducted on energy efficient cache buffer management for disk based storage systems. Some of them use greedy prefetching technique to artificially increase disk idle intervals if there are a large number of known future requests. However, this might result in sub-optimal solution by not exploiting the relationship between I/O access pattern (sequential/random) and application pattern (CPU required for computing time). In a CPU-bound application, by explicitly taking into account this relationship it may reduce energy conservation by up to 50% and increase power cycle number by 100% compared to an existing efficient prefetching scheme without this consideration. In this paper, we consider the tradeoff between disk power consumption, performance guarantee and disk reliability all together by proposing a Disk characteristic based Power-Optimal Prefetching (DiscPOP) scheme. Specifically, we make two contributions: (i) A theoretical model is conducted to analyze energy-efficient cache buffer management in disk I/O system and it is formulated as an optimization problem. We have shown it can be solved via an Integer Linear Programming (ILP) technique. (ii) We propose a simple Divide-and-Conquer based offline algorithm named Greedy Partition (GP) to divide the problem into several small ones and solve them separately via an ILP solver. We use trace-driven simulations to evaluate our proposed scheme. The results show GP outperforms the traditional aggressive prefetching by up to 29.2% more disk energy conservation and 20.6% power cycle reduction. <s> BIB009 </s> Cloud Computing: Survey on Energy Efficiency <s> Storage Systems. <s> Cloud storage is a hot topic at the moment with Google's Google Storage, Microsoft's Sky Drive, iCloud, Drop box, Mozy and dozens of others. Because of these applications, conserving energy of storage systems is becoming a growing concern in current storage technology. The factors of disk power consumption include disk idle time, poor random writing performance and random read in distributed file systems. Hence, we present an adaptive write cache mechanism - Cache RAID. Redundant Arrays of Inexpensive Disk (RAID) is widely used in modern distributed storage systems. Our Cache RAID aims to improve the random access problems that implicitly exist in RAID techniques to create more idle time of hard drives, and conserve RAID disk array energy. The experimental results show that Cache RAID storage system can conserved 50%~70% of the power consumption compared to the conventional software RAID system. <s> BIB010 </s> Cloud Computing: Survey on Energy Efficiency <s> Storage Systems. <s> As data-intensive, network-based applications proliferate, the power consumed by the data-center storage subsystem surges. This survey summarizes, organizes, and integrates a decade of research on power-aware enterprise storage systems. All of the existing power-reduction techniques are classified according to the disk-power factor and storage-stack layer addressed. A majority of power-reduction techniques is based on dynamic power management. We also consider alternative methods that reduce disk access time, conserve space, or exploit energy-efficient storage hardware. For every energy-conservation technique, the fundamental trade-offs between power, capacity, performance, and dependability are uncovered. With this survey, we intend to stimulate integration of different power-reduction techniques in new energy-efficient file and storage systems. <s> BIB011 </s> Cloud Computing: Survey on Energy Efficiency <s> Storage Systems. <s> The energy consumption related to data centers is ever increasing, despite the significant efficiency improvements in the involved technologies and the economic crisis. Pervasive adoption of virtualization, decreasing of PUE as well as new features related to energy-efficiency are not able to stop this growth trend, mainly sustained from the explosion of cloud services in both the fixed and mobile ICT markets. One of the most important factors that contributes to the increase in the data center energy demand is the evolution of data utilization in cloud environments. Big data support is one of the main driver of this process, new data sources continuously produce huge amounts of mostly unstructured data, that should be stored in large centralized storage systems to be accessed by the cloud users and analyzed by the companies in real time. This has a disruptive effect for the energy consumption of the data center hosting the above storage resources, that's why the data need to be stored and analyzed in IOPS intensive style. Flash memory technologies can play a key role in such scenario, since they can reduce dramatically both the storage footprint and energy consumption and increase applications performances bringing appreciable economic benefits. This fundamental efficiency and performance improvement for storage architectures can't be supported by legacy technologies because they are not designed to use flash technologies but rather they are based on energy-hungry legacy mechanical disks. That is limit the energy efficiency and performance delivered by solid state disks (SSD) installed in legacy storage systems, opening the door to the development of new technologies that will be able to fully exploit the potential of flash disks. The aim of this work is presenting a brief survey about the potential of flash technologies for improving the energy efficiency of data center storage systems supporting the incoming Big Data services. <s> BIB012
In addition to optimizing the cache subsystem itself, the cache can be used to achieve energy efficiency goals for other subsystems such as storage disks. BIB010 exploit the catching scheme to improve the energy efficiency of RAID disk systems. Along with energy efficiency, BIB008 also consider disk reliability. And, in addition to disk reliability, lifetime and performance of a cache memory that is implemented using SSD is considered in BIB004 . Instead of using aggressive prefetching, BIB009 present DiscPOP, a power-aware buffer management method that populates cache by exploiting the relationship between I/O access and application pattern behavior, which includes information from the CMS and Appliance domain. Another example of smart prefetching is presented in BIB001 , where the authors extend data disk idle mode by populating cache memory with bursty pattern disk access. A similar approach is researched in BIB005 , where the authors suggest redirecting I/O requests to disk buffers instead of to data disks. Using a prefetching scheme also applies in the disk buffers approach shown in BIB002 . A further step in using buffers is suggested by BIB006 by combining a buffer disk approach with a cache approach. They use a flash memory cache on top of disk buffers to store most popular data, thus providing fast access to this data without affecting the disks. BIB003 also combine memorylevel (cache) and disk-level (RAID) redundancy in order to save energy. These papers, along with BIB011 and  , provide a good overview of relevant work done in the field of storage disk energy efficiency. Moreover, SSD disks and their utilization in energy-efficient storage systems are discussed in BIB012 , whereas HDD technology is discussed in BIB007 .