Disk Power Management Research Articles

Lifetime and QoS-aware energy-saving buffering schemes

The heterogeneous drive (HDrive), which combines solid-state disk (SSD) and HDD, brings opportunity for energy-saving and has received extensive attention recently. This paper focuses on the file buffering schemes and adaptive disk power management (DPM) scheme for HDrive. As for the first issue, we propose a frequency–energy based replacement (FEBR) scheme based on an energy-cost model; as for the second issue, we present a sliding-window based adaptive DPM scheme by taking the HDD's lifetime into account. To make the trade-off among performance, HDD's lifetime and energy-saving, we contrive a QoS-aware DPM scheme. With extensive experiments on four real-world traces, we have evaluated the effectiveness of existing replacement schemes on energy-efficiency, performance, and HDD's lifetime and compare with our proposed schemes. The experimental results have demonstrated that energy-saving in HDrive is feasible and can reach as high as 60–80%, and that FBR and its variant FEBR, and GDS are the best ones among all those online schemes evaluated while FEBR has some advantage over FBR and GDS on the whole. The results have also revealed that our proposed adaptive sliding-window-based DPM scheme can effectively control the disk's lifetime and the QoS-aware DPM scheme works well in making tradeoffs among performance, HDD's lifetime and energy-saving.

Selective frame prefetching for reducing disk energy consumption in scalable video coding (SVC) media players

We propose a new disk power management scheme for scalable video coding (SVC) video playback. Conventional disk power management techniques for video players usually prefetch video frames into buffer to allow disk to enter low-power mode, which may require significant buffer space. To address this, we exploit temporal scalability property in which multiple frame rates for the same video stream are provided, and allow selective frame prefetching with the aim of achieving specified quality levels while reducing disk energy consumption. Simulation results show that the disk energy consumption can be reduced by 8.4% on average without any noticeable quality degradation by users.

An Improved Compiler Directed Power Optimization for Disk Based Systems using Back Propagation Neural Networks

The performance of the parallel disk systems is highly affected by excessive power consumption. Hence, various researches are being done in the areas of energy optimization of such systems. Because of the extensive growth and development of computer applications, there has been a huge transformation in the disk subsystem, which mainly includes larger number of disks with higher storage capacities and rotational speeds. Hence, Disk power management has become an essential area of research in recent years as it utilizes very high power. An advanced compiler-directed disk power management approach is presented in this paper which exploits disk access approaches for minimizing energy consumption. This paper examines the various disk access techniques and chooses the optimal approach which would offer better overall performance of the disks via Back Propagation neural network technique which is trained using Modified Levenberg Morquat learning. The experimental evaluation shows that the proposed technique offers better power consumption than the traditional approaches.

Adaptive disk power management for portable media players

To support the large storage requirements, consumer electronics for video playback are increasingly being equipped with hard disk drives (HDD) that consume a significant amount of energy. A video player may prefetch many frames to give disk an opportunity to go to standby mode, but this may cause playback to be distorted or stopped if timely power mode transitions are not incorporated. We present the design, implementation and evaluation of a data prefetching scheme for energy-aware video data retrieval for portable media players (PMP). We formulate the problem when the prefetching is used for variable-bit-rate (VBR) streams to reduce disk energy consumption and then propose a new energy-aware data retrieval scheme that prefetches video data in a just-in-time way so as to increase the period in which disk stays in standby mode while guaranteeing the real-time service. We implemented our scheme in the legacy video player called Mplayer that is typically used for Linux-based consumer devices. Experimental results show that it saves energy as much as 51% compared with conventional schemes.

Compiler-Directed Energy Optimization for Parallel Disk Based Systems

Disk subsystem is known to be a major contributor to overall power consumption of high-end parallel systems. Past research proposed several architectural-level techniques to reduce disk power by taking advantage of idle periods experienced by disks. Although such techniques have been known to be effective in certain cases, they share a common drawback: they operate in a reactive manner, i.e., they control disk power by observing past disk activity (for example, idle and active periods) and estimating future ones. Consequently, they can miss opportunities for saving power and incur significant performance penalties due to inaccuracies in predicting idle and active times. Motivated by this observation, this paper proposes and evaluates a compiler-driven approach to reducing disk power consumption of array-based scientific applications executing on parallel architectures. The proposed approach exposes disk layout information to the compiler, allowing it to derive the disk access pattern, i.e., the order in which parallel disks are accessed. This paper demonstrates two uses of this information. First, we can implement proactive disk power management, i.e., we can select the most appropriate power-saving strategy and disk-preactivation strategy based on the compiler-predicted future idle and active periods of parallel disks. Second, we can restructure the application code to increase the length of idle disk periods, which leads to better exploitation of available power-saving capabilities. We implemented both these approaches within an optimizing compiler and tested their effectiveness using a set of benchmark codes from the Spec 2000 suite and a disk power simulator. Our results show that the compiler-driven disk power management is very promising. The experimental results also reveal that, although proactive disk power management is very effective, code restructuring for disk power achieves additional energy savings across all the benchmarks tested, and these savings are very close to optimal savings that can be obtained through an integer linear programming (ILP)-based scheme.

Power-Aware Storage Cache Management

Reducing energy consumption is an important issue for data centers. Among the various components of a data center, storage is one of the biggest energy consumers. Previous studies have shown that the average idle period for a server disk in a data center is very small compared to the time taken to spin down and spin up. This significantly limits the effectiveness of disk power management schemes. This article proposes several power-aware storage cache management algorithms that provide more opportunities for the underlying disk power management schemes to save energy. More specifically, we present an offline energy-optimal cache replacement algorithm using dynamic programming, which minimizes the disk energy consumption. We also present an offline power-aware greedy algorithm that is more energy-efficient than Belady's offline algorithm (which minimizes cache misses only). We also propose two online power-aware algorithms, PA-LRU and PB-LRU. Simulation results with both a real system and synthetic workloads show that, compared to LRU, our online algorithms can save up to 22 percent more disk energy and provide up to 64 percent better average response time. We have also investigated the effects of four storage cache write policies on disk energy consumption.

DRPM

A large portion of the power budget in server environments goes into the I/O subsystem - the disk array in particular. Traditional approaches to disk power management involve completely stopping the disk rotation, which can take a considerable amount of time, making them less useful in cases where idle times between disk requests may not be long enough to outweigh the overheads. This paper presents a new approach called DRPM to modulate disk speed (RPM) dynamically, and gives a practical implementation to exploit this mechanism. Extensive simulations with different workload and hardware parameters show that DRPM can provide significant energy savings without compromising much on performance. This paper also discusses practical issues when implementing DRPM on server disks.