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Client-side resource management on the cloud: survey and future directions created by Marc Eduard Frincu, Stéphane Genaud and Julien Gossa

By: Contributor(s): Material type: TextTextSeries: International journal of cloud computing ; Volume , number ,United Kingdom: Inderscience, 2015Content type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISSN:
  • 2043-9989
Subject(s): LOC classification:
  • QA76.S85 INT
Online resources: Abstract: Cloud computing and how to bridge the gap between various providers is getting increasing attention. In this context, efficiently scheduling tasks on heterogeneous resources is of extreme importance. The state-of-the-art for this field has been continuously growing during the last years and has reached a point in which a comprehensive overview indicating current solutions and ongoing challenges is of extreme importance for researchers. This paper aims to offer this analysis from a client-side scheduling perspective in which emphasis is not put on physical resource selection but on task to virtual machine mappings and virtual machine allocation. It provides a taxonomy for the current state-of-the-art and a unified model concerning the various metrics and goals used throughout literature. This model is designed to be sufficiently generic, extensible, and comprehensive to support most of the future work in the field. Several promising research directions and existing challenges are described.
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Item type Current library Call number Vol info Status Notes Date due Barcode
Journal Article Journal Article Main Library - Special Collections QA76.S85 INT (Browse shelf(Opens below)) Vol. 4, no.3 (pages234-257) Not for loan For in house use only

Cloud computing and how to bridge the gap between various providers is getting increasing attention. In this context, efficiently scheduling tasks on heterogeneous resources is of extreme importance. The state-of-the-art for this field has been continuously growing during the last years and has reached a point in which a comprehensive overview indicating current solutions and ongoing challenges is of extreme importance for researchers. This paper aims to offer this analysis from a client-side scheduling perspective in which emphasis is not put on physical resource selection but on task to virtual machine mappings and virtual machine allocation. It provides a taxonomy for the current state-of-the-art and a unified model concerning the various metrics and goals used throughout literature. This model is designed to be sufficiently generic, extensible, and comprehensive to support most of the future work in the field. Several promising research directions and existing challenges are described.

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