Disk Power Management Schemes 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.

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.