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Software Engineering for Self-Adaptive Systems II pp 354–375Cite as

Hierarchical Self-Optimization of SaaS Applications in Clouds

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7475))

Abstract

This chapter introduces a framework and a methodology to manage a SaaS application on top of a PaaS infrastructure. This framework utilizes PaaS policy sets to implement the SaaS provider’s elasticity policy for its application server tier. Adaptation is based on strategy-trees, which allow for systematic capture, representation and reasoning about adaptation variability, based on hierarchically organizing different levels of temporal granularity. Thus, a strategy-tree is utilized at the SaaS layer to actively guide policy set selection at runtime in order to maintain alignment with the SaaS provider’s business objectives. This way, the SaaS provider’s attitudes and preferences reflecting their general business needs are incorporated into the adaptation mechanism in an organized and accessible manner. Results from an experiment conducted on a real cloud are presented in support of this approach.

This is an extended version of a short paper published previously: B. Simmons, H. Ghanbari, M. Litoiu and G. Iszlai, ”Managing a SaaS application in the cloud using PaaS policy sets and a strategy-tree,” Network and Service Management (CNSM), 2011 7th International Conference on, vol., no., pp.1-5, 24-28 Oct. 2011. “Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than IFIP must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.”

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Author information

Authors and Affiliations

  1. York University, 4700 Keele Street, Toronto, Canada

    Bradley Simmons, Hamoun Ghanbari, Sotirios Liaskos & Marin Litoiu

  2. Toronto Software Lab., IBM, 8200 Warden Avenue, Markham, Canada

    Gabriel Iszlai

Authors
  1. Bradley Simmons
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  2. Hamoun Ghanbari
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  3. Sotirios Liaskos
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  4. Marin Litoiu
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  5. Gabriel Iszlai
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Editor information

Editors and Affiliations

  1. School of Computing, University of Kent, Kent CT2 7NF, Canterbury, UK

    Rogério de Lemos

  2. System Analysis and Modeling Group, Hasso Plattner Institute at the University of Potsdam, Germany

    Holger Giese

  3. University of Victoria, Australia

    Hausi A. Müller

  4. Institute for Software Research, School of Computer Science, Carnegie Mellon University, 15213, Pittsburgh, PA, USA

    Mary Shaw

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Simmons, B., Ghanbari, H., Liaskos, S., Litoiu, M., Iszlai, G. (2013). Hierarchical Self-Optimization of SaaS Applications in Clouds. In: de Lemos, R., Giese, H., Müller, H.A., Shaw, M. (eds) Software Engineering for Self-Adaptive Systems II. Lecture Notes in Computer Science, vol 7475. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35813-5_14

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  • DOI: https://doi.org/10.1007/978-3-642-35813-5_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35812-8

  • Online ISBN: 978-3-642-35813-5

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