当前位置: X-MOL 学术Simul. Model. Pract. Theory › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
An intelligent energy efficient storage system for cloud based big data applications
Simulation Modelling Practice and Theory ( IF 4.2 ) Pub Date : 2020-12-28 , DOI: 10.1016/j.simpat.2020.102260
Sumedha Arora , Anju Bala

Storage technology has emerged as an indispensable paradigm for processing various applications in cloud data centers. The storage infrastructure consisting of Hard Disk Drives (HDDs) and Solid-State Drives (SSDs) accounts for high energy consumption. Also, the trade-offs between HDDs and SSDs in terms of cost and energy consumption are extremely high. Therefore, disk-based storage subsystems need to be more energy efficient. This paper proposes an intelligent energy-efficient hybrid disk storage system. The proposed system recognizes the frequently used data from traces of applications. Replica management along with data layout is used to allocate frequently used files in hot disks and the other files in cold disks. The request is executed using an intelligent scheduling technique that searches and selects the disk based on its states. The scheduling technique selects either an idle or active disk without spinning the standby disks. The selection procedure also considers minimum waiting time for the active disk and maximum remaining idle time for the idle disk. The proposed system has been implemented by adding disk management in the cloud environment, which proved to be highly effective in achieving a 39% power savings with an 18.26% decrease in execution time.



中文翻译:

用于基于云的大数据应用程序的智能节能存储系统

存储技术已经成为处理云数据中心中各种应用程序必不可少的范例。由硬盘驱动器(HDD)和固态驱动器(SSD)组成的存储基础架构导致了高能耗。而且,在成本和能耗方面,HDD和SSD之间的权衡非常高。因此,基于磁盘的存储子系统需要更加节能。本文提出了一种智能节能混合磁盘存储系统。所提出的系统从应用程序的痕迹中识别出经常使用的数据。副本管理以及数据布局用于在热磁盘中分配经常使用的文件,在冷磁盘中分配其他文件。该请求使用智能调度技术执行,该技术根据磁盘的状态搜索并选择磁盘。调度技术选择空闲磁盘或活动磁盘而不旋转备用磁盘。选择过程还考虑了活动磁盘的最短等待时间和空闲磁盘的最大剩余空闲时间。通过在云环境中添加磁盘管理来实现所提出的系统,事实证明,这种管理在节省39%的电能,执行时间减少18.26%方面非常有效。

更新日期:2020-12-31
down
wechat
bug