QoS-based storage resources provisioning for grid applications

  • Authors:

  • Kornel SkałKowski;Renata SłOta;Dariusz KróL;Jacek Kitowski

  • Affiliations:

  • AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of Computer Science, al. Mickiewicza 30, 30-059, Kraków, ...;AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of Computer Science, al. Mickiewicza 30, 30-059, Kraków, ...;AGH University of Science and Technology, ACC Cyfronet AGH, ul. Nawojki 11, 30-950 Kraków, Poland;AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of Computer Science, al. Mickiewicza 30, 30-059, Kraków, ...

  • Venue:
  • Future Generation Computer Systems
  • Year:
  • 2013

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Abstract

In recent years, distributed environments such as grids and clouds have evolved quickly and become widely used for both business and scientific purposes. Grid environments are used for solving increasingly complex problems in order to provide more accurate and up-to-date results. However, evolution of modern grid middlewares does not follow current trends in their utilization, which often leads to problems concerning provisioning of resources in grid environments. Many users of grid systems stumble on performance issues during execution of their applications. A special kind of grid applications which are dependent on effective provisioning of storage resources constitute data-intensive grid applications, i.e. applications which operate on large datasets. This paper addresses the issue of effective provisioning of storage resources for data-intensive grid applications based on the best-effort strategy. In order to cater applications demand on storage resources in heterogeneous and dynamic grid environments, we propose an approach relying on a combination of a cluster file system technology, a dedicated storage resources monitoring service and a management layer. The paper describes the way that this combination of technologies solves the issue of effective storage resources provisioning in grid environments by presentation of the FiVO/QStorMan toolkit, which constitutes an implementation of the proposed approach. In order to prove that the proposed approach actually reduces data-intensive applications execution time, extensive evaluation of the framework is presented for motivating scenarios which overlap most kinds of data-intensive applications.