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

Du, Zhihui; Fan, Wenjun; Chai, Yunpeng y 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.

Descripción

Título: Priori information and sliding window based prediction algorithm for energy-efficient storage systems in cloud
Autor/es:
  • Du, Zhihui
  • Fan, Wenjun
  • Chai, Yunpeng
  • Chen, Yinong
Tipo de Documento: Artículo
Título de Revista/Publicación: Simulation Modelling Practice and Theory
Fecha: 29 Junio 2013
Volumen: 39
Materias:
Palabras Clave Informales: Energy conservation, prediction algorithm, cloud computing
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Ingeniería de Sistemas Telemáticos [hasta 2014]
Licencias Creative Commons: Reconocimiento

Texto completo

[img]
Vista Previa
PDF (Document Portable Format) - Se necesita un visor de ficheros PDF, como GSview, Xpdf o Adobe Acrobat Reader
Descargar (1MB) | Vista Previa

Resumen

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.

Más información

ID de Registro: 45394
Identificador DC: http://oa.upm.es/45394/
Identificador OAI: oai:oa.upm.es:45394
Identificador DOI: 10.1016/j.simpat.2013.06.002
URL Oficial: http://www.sciencedirect.com/science/article/pii/S1569190X13000932
Depositado por: Wenjun Fan
Depositado el: 18 Abr 2017 12:58
Ultima Modificación: 18 Abr 2017 12:59
  • Open Access
  • Open Access
  • Sherpa-Romeo
    Compruebe si la revista anglosajona en la que ha publicado un artículo permite también su publicación en abierto.
  • Dulcinea
    Compruebe si la revista española en la que ha publicado un artículo permite también su publicación en abierto.
  • Recolecta
  • e-ciencia
  • Observatorio I+D+i UPM
  • OpenCourseWare UPM