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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-29619
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dc.contributor.authorPatros, Panos-
dc.contributor.authorSpillner, Josef-
dc.contributor.authorPapadopoulos, Alessandro V.-
dc.contributor.authorVarghese, Blesson-
dc.contributor.authorRana, Omer-
dc.contributor.authorDustdar, Schahram-
dc.date.accessioned2024-01-19T08:03:03Z-
dc.date.available2024-01-19T08:03:03Z-
dc.date.issued2021-11-01-
dc.identifier.issn1089-7801de_CH
dc.identifier.issn1941-0131de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/29619-
dc.description.abstractAlthough serverless computing generally involves executing short-lived "functions", the increasing migration to this computing paradigm requires careful consideration of energy and power requirements. Serverless computing is also viewed as an economically-driven computational approach, often influenced by the cost of computation, as users are charged for per-sub-second use of computational resources rather than the coarse-grained charging that is common with virtual machines and containers. To ensure that the startup times of serverless functions do not discourage their use, resource providers need to keep these functions hot, often by passing in synthetic data. We describe the real power consumption characteristics of serverless, based on execution traces reported in the literature, and describe potential strategies (some adopted from existing VM and container-based approaches) that can be used to reduce the energy overheads of serverless execution. Our analysis is, purposefully, biased towards the use of machine learning workloads as: (i) such workloads are increasingly being used widely across different applications; (ii) functions that implement machine learning algorithms can range in complexity from long-running (deep learning) vs. short-running (inference only), enabling us to consider serverless across a variety of possible execution behaviours. The general findings are also easily translatable to other domains.de_CH
dc.language.isoende_CH
dc.publisherIEEEde_CH
dc.relation.ispartofIEEE Internet Computingde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectServerlessde_CH
dc.subjectSustainabilityde_CH
dc.subjectGreen computingde_CH
dc.subject.ddc004: Informatikde_CH
dc.titleToward sustainable serverless computingde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
dc.identifier.doi10.1109/MIC.2021.3093105de_CH
dc.identifier.doi10.21256/zhaw-29619-
zhaw.funding.euNode_CH
zhaw.issue6de_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end50de_CH
zhaw.pages.start42de_CH
zhaw.publication.statusacceptedVersionde_CH
zhaw.volume25de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedService Engineeringde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Patros, P., Spillner, J., Papadopoulos, A. V., Varghese, B., Rana, O., & Dustdar, S. (2021). Toward sustainable serverless computing. IEEE Internet Computing, 25(6), 42–50. https://doi.org/10.1109/MIC.2021.3093105
Patros, P. et al. (2021) ‘Toward sustainable serverless computing’, IEEE Internet Computing, 25(6), pp. 42–50. Available at: https://doi.org/10.1109/MIC.2021.3093105.
P. Patros, J. Spillner, A. V. Papadopoulos, B. Varghese, O. Rana, and S. Dustdar, “Toward sustainable serverless computing,” IEEE Internet Computing, vol. 25, no. 6, pp. 42–50, Nov. 2021, doi: 10.1109/MIC.2021.3093105.
PATROS, Panos, Josef SPILLNER, Alessandro V. PAPADOPOULOS, Blesson VARGHESE, Omer RANA und Schahram DUSTDAR, 2021. Toward sustainable serverless computing. IEEE Internet Computing. 1 November 2021. Bd. 25, Nr. 6, S. 42–50. DOI 10.1109/MIC.2021.3093105
Patros, Panos, Josef Spillner, Alessandro V. Papadopoulos, Blesson Varghese, Omer Rana, and Schahram Dustdar. 2021. “Toward Sustainable Serverless Computing.” IEEE Internet Computing 25 (6): 42–50. https://doi.org/10.1109/MIC.2021.3093105.
Patros, Panos, et al. “Toward Sustainable Serverless Computing.” IEEE Internet Computing, vol. 25, no. 6, Nov. 2021, pp. 42–50, https://doi.org/10.1109/MIC.2021.3093105.


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