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Resource Scaling Performance for Cache Intensive Algorithms in Windows Azure

  • Conference paper
Intelligent Distributed Computing VII

Part of the book series: Studies in Computational Intelligence ((SCI,volume 511))

Abstract

Customers usually expect linear performance increase for increased demand for renting resources from cloud. However, it is not always the case, although the cloud service provider offers the specified infrastructure. The real expectation is limited due to memory access type, how data fits in available cache, nature of programs (if they are computation-intensive, memory or cache demanding and intensive) etc. Cloud infrastructure in addition rises new challenges by offered resources via virtual machines. The ongoing open question is choosing what is better - usage of parallelization with more resources or spreading the job among several instances of virtual machines with less resources. In this paper we analyze behavior of Microsoft Windows Azure Cloud on different loads. We find the best way to scale the resources to speedup the calculations and obtain best performance for cache intensive algorithms.

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Author information

Authors and Affiliations

  1. Faculty of Information Sciences and Computer Engineering, Ss. Cyril and Methodious University, Rugjer Boshkovikj 16, 1000, Skoipje, Macedonia

    Marjan Gusev & Sasko Ristov

Authors
  1. Marjan Gusev
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  2. Sasko Ristov
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Corresponding author

Correspondence to Marjan Gusev .

Editor information

Editors and Affiliations

  1. Faculty of Mathematics and Physics, Charles University in Prague, Prague, Czech Republic

    Filip Zavoral

  2. Department of Computer Engineering, Yeungnam University, Gyeingsan, Korea, Republic of (South Korea)

    Jason J. Jung

  3. Faculty of Automatics, Computers and Electronics, University of Craiova Software Engineering Department, Craiova, Romania

    Costin Badica

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© 2014 Springer International Publishing Switzerland

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Gusev, M., Ristov, S. (2014). Resource Scaling Performance for Cache Intensive Algorithms in Windows Azure. In: Zavoral, F., Jung, J., Badica, C. (eds) Intelligent Distributed Computing VII. Studies in Computational Intelligence, vol 511. Springer, Cham. https://doi.org/10.1007/978-3-319-01571-2_10

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  • DOI: https://doi.org/10.1007/978-3-319-01571-2_10

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01570-5

  • Online ISBN: 978-3-319-01571-2

  • eBook Packages: EngineeringEngineering (R0)

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