Power-Effective File Layout Based on Large Scale Data-Intensive Application in Virtualized Environment

Abstract

SUMMARYIn data centers, large numbers of computers are run simultaneously. These computers consume an enormous amount of energy. Several challenges related to this issue have been published. An energyefficient storage management method that cooperates with applications was one effective approach. In this method, data and storage devices are managed using application support and the power consumption of storage devices is significantly decreased. However, existing studies do not take the virtualized environment into account. Recently, many data-intensive applications have been run in a virtualized environment, such as the cloud computing environment. In this paper, we focus on a virtualized environment wherein multiple virtual machines run on a physical computer and a data intensive application runs on each virtual machine. We discuss a method for reducing storage device power consumption using application support. First, we propose two storage management methods using application information. One method optimizes the inter-HDD file layout. This method removes frequently-accessed files from a certain HDD and switches the HDD to power-off mode. To balance loads and reduce seek distances, this method separates a heavily accessed file and consolidates files in a virtual machine with low access frequency. The other method optimizes the intra-HDD file layout, in addition to performing inter-HDD optimization. This method places frequently accessed files near each other. Second, we present our experimental results and demonstrate that the proposed methods can create sufficiently long HDD access intervals that power-off mode can be used, and thereby, reduce the power consumption of storage devices.

BET Estimation on Power Saving by Intermittent Disabling Network Interface on Android

“…This is a naive method that is achieved by straightforwardly applying the BET estimating method in Refs. [8], [9].…”

“…Work of Refs. [8], [9] proposed the methods for reducing the power consumption of storage devices by frequently bringing the device to power-off mode. This paper is based on the idea of these previous work, which is intermitted usage of the device, and some papers mentioned BET.…”

“…For example, the studies of Refs. [7], [8], [9] demonstrated that the method was effective for hard disk drives 1 Kogakuin University, Shinjuku, Tokyo 163-8677, Japan 2 R&D Center for Smart Mobility, Kyushu University, Fukuoka 819-0395, Japan 3 Kyushu University, Fukuoka 819-0395, Japan 4 Ochanomizu University, Bunkyo, Tokyo 112-8610, Japan a) sane@cc.kogakuin.ac.jp (HDDs).…”

An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments

“…Thus, there is no guarantee that awakened nodes can provide the required sensors. In Cloud Computing literature, there are already works on resource allocation, such as [ 31 , 32 ], in which they also consider the optimal selection of resources in datacenters (like virtual machines, storage disks, and memories) to save energy consumption. Although similar to virtual sensor provisioning, the algorithms found in cloud computing context cannot be used in sensor cloud, since they do not take into account the constrained and specifics characteristics of a WSN (such as the small processing capability and limited energy supply).…”

Analysis of Optimal File Placement for Energy-Efficient File-Sharing Cloud Storage System

“…By laying such infrequently accessed data on a subset of hard disks and spinning down the disks, the storage energy consumption can be reduced significantly. Many studies on storage energy conservation techniques follow the idea of PDC and successfully reduce the energy consumptions of hard disk-based storage systems [6] [12]. Two essential functions in the implementation of PDC are the prediction of data access frequencies and the data placement method.…”