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OTM Confederated International Conferences "On the Move to Meaningful Internet Systems"

OTM 2017: On the Move to Meaningful Internet Systems. OTM 2017 Conferences pp 370–388Cite as

SmartGC: Online Memory Management Prediction for PaaS Cloud Models

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10573))

Abstract

In Platform-as-a-Service clouds (public and private) an efficient resource management of several managed runtimes involves limiting the heap size of some VMs so that extra memory can be assigned to higher priority workloads. However, this should not be done in an application-oblivious way because performance degradation must be minimized. Also, each tenant tends to repeat the execution of applications with similar memory-usage patterns, giving opportunity to reuse parameters known to work well for a given workload. This paper presents SmartGC, a system to determine, at runtime, the best values for critical heap management parameters of JVMs. SmartGC comprises two main phases: (1) a training phase where it collects, with different heap resizing policies, representative execution metrics during the lifespan of a workload; and (2) an execution phase where it matches the execution parameters of new workloads against those of already seen workloads, and enforces the best heap resizing policy. Distinctly from other works, this is done without a previous analysis of unknown workloads. Using representative applications, we show that our approach can lead to memory savings, even when compared with a state-of-the-art virtual machine - OpenJDK. Furthermore, we show that we can predict with high accuracy the best heap policy in a relatively short period of time and with a negligible runtime overhead. Although we focus on the heap resizing, this same approach could also be used to adapt other parameters or even the GC algorithm.

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Notes

  1. 1.

    http://cloud.google.com/appengine.

  2. 2.

    http://jikesrvm.org/Experimental+Guidelines.

  3. 3.

    http://www.cs.waikato.ac.nz/~ml/weka/index.html.

  4. 4.

    Using –with-perfevents parameter in buildit script.

  5. 5.

    http://perfmon2.sourceforge.net/.

  6. 6.

    http://jikesrvm.org/Experimental+Guidelines.

  7. 7.

    Because we have 10 final average samples we used the Students t-distribution to calculate the confidence interval [13].

  8. 8.

    https://www.spec.org/jvm2008.

  9. 9.

    http://www.dacapobench.org.

  10. 10.

    https://www.vmware.com/support/pubs/vfabric-em4j.html.

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Acknowledgements

This work was supported by national funds through Fundação para a Ciência e a Tecnologia with reference PTDC/EEI-SCR/6945/2014, and by the ERDF through COMPETE 2020 Programme, within project POCI-01-0145-FEDER-016883. This work was partially supported by Instituto Superior de Engenharia de Lisboa and Instituto Politécnico de Lisboa. This work was supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with reference UID/CEC/50021/2013.

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Authors and Affiliations

  1. INESC-ID Lisboa, Lisbon, Portugal

    José Simão, Sérgio Esteves & Luís Veiga

  2. Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal

    Sérgio Esteves & Luís Veiga

  3. Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Lisbon, Portugal

    José Simão

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  1. José Simão
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  2. Sérgio Esteves
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Correspondence to José Simão .

Editor information

Editors and Affiliations

  1. University of Lorraine, Nancy, France

    Hervé Panetto

  2. Odisee University College, Brussels, Belgium

    Christophe Debruyne

  3. Télécom SudParis, Évry, France

    Walid Gaaloul

  4. Tilburg University, Tilburg, The Netherlands

    Mike Papazoglou

  5. Freie Universität Berlin and Fraunhofer FOKUS, Berlin, Germany

    Adrian Paschke

  6. Università degli Studi di Milano, Crema, Italy

    Claudio Agostino Ardagna

  7. TU Graz, Graz, Austria

    Robert Meersman

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Simão, J., Esteves, S., Veiga, L. (2017). SmartGC: Online Memory Management Prediction for PaaS Cloud Models. In: Panetto, H., et al. On the Move to Meaningful Internet Systems. OTM 2017 Conferences. OTM 2017. Lecture Notes in Computer Science(), vol 10573. Springer, Cham. https://doi.org/10.1007/978-3-319-69462-7_25

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  • DOI: https://doi.org/10.1007/978-3-319-69462-7_25

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