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Improving OLAM with Cloud Elasticity

  • Guilherme Galante
  • Luis Carlos Erpen De Bona
  • Claudio Schepke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8584)

Abstract

Elasticity is considered one of the fundamental properties of cloud computing, and can be seen as the ability of a system to increase or decrease the computing resources allocated in a dynamic and on demand way. This feature is suitable for dynamic applications, whose resources requirements cannot be determined exactly in advance, either due to changes in runtime requirements or in application structure. A good candidate for using cloud elasticity is the Ocean-Land-Atmosphere Model (OLAM), since it presents a significant load variation during its execution and due to online mesh refinement (OMR), that causes load unbalancing problems. In this paper, we present our efforts to adapt OLAM to use the elasticity offered in cloud environments to dynamic allocate resources according to the demands of each execution phase, and to minimize the load unbalancing caused by OMR. The results show that elasticity was successfully used to provide these features, improving the OLAM performance and providing a better use of resources.

Keywords

Ocean-Land-Atmosphere Model Cloud Computing Elasticity Load Balancing Cloudine Framework 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Guilherme Galante
    • 1
    • 2
  • Luis Carlos Erpen De Bona
    • 1
  • Claudio Schepke
    • 3
  1. 1.Federal University of Paraná - UFPRCuritibaBrazil
  2. 2.Western Paraná State University - UnioesteCascavelBrazil
  3. 3.Federal University of Pampa - UNIPAMPAAlegreteBrazil

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