Priori information and sliding window based prediction algorithm for energy-efficient storage systems in cloud

Du, Zhihui and Fan, Wenjun and Chai, Yunpeng and Chen, Yinong (2013). Priori information and sliding window based prediction algorithm for energy-efficient storage systems in cloud. "Simulation Modelling Practice and Theory", v. 39 ; pp.. ISSN 1569-190X. https://doi.org/10.1016/j.simpat.2013.06.002.

Description

Title: Priori information and sliding window based prediction algorithm for energy-efficient storage systems in cloud
Author/s:
  • Du, Zhihui
  • Fan, Wenjun
  • Chai, Yunpeng
  • Chen, Yinong
Item Type: Article
Título de Revista/Publicación: Simulation Modelling Practice and Theory
Date: 29 June 2013
ISSN: 1569-190X
Volume: 39
Subjects:
Freetext Keywords: Energy conservation, prediction algorithm, cloud computing
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería de Sistemas Telemáticos [hasta 2014]
Creative Commons Licenses: Recognition

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Abstract

One of the major challenges in cloud computing and data centers is the energy conservation and emission reduction. Accurate prediction algorithms are essential for building energy efficient storage systems in cloud computing. In this paper, we first propose a Three-State Disk Model (3SDM), which can describe the service quality and energy consumption states of a storage system accurately. Based on this model, we develop a method for achieving energy conservation without losing quality by skewing the workload among the disks to transmit the disk states of a storage system. The efficiency of this method is highly dependent on the accuracy of the information predicting the blocks to be accessed and the blocks not be accessed in the near future. We develop a priori information and sliding window based prediction (PISWP) algorithm by taking advantage of the priori information about human behavior and selecting suitable size of sliding window. The PISWP method targets at streaming media applications, but we also check its efficiency on other two applications, news in webpage and new tool released. Disksim, an established storage system simulator, is applied in our experiments to verify the effect of our method for various users’ traces. The results show that this prediction method can bring a high degree energy saving for storage systems in cloud computing environment.

More information

Item ID: 45394
DC Identifier: http://oa.upm.es/45394/
OAI Identifier: oai:oa.upm.es:45394
DOI: 10.1016/j.simpat.2013.06.002
Official URL: http://www.sciencedirect.com/science/article/pii/S1569190X13000932
Deposited by: Wenjun Fan
Deposited on: 18 Apr 2017 12:58
Last Modified: 18 Apr 2017 12:59
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