Szczegóły publikacji

Opis bibliograficzny

Challenges for scheduling scientific workflows on cloud functions / Joanna Kijak, Piotr Martyna, Maciej PAWLIK, Bartosz BALIŚ, Maciej MALAWSKI // W: IEEE CLOUD 2018 [Dokument elektroniczny] : 2018 IEEE international conference on Cloud computing : 2–7 July 2018, San Francisco, USA : proceedings. — Wersja do Windows. — Dane tekstowe. — Piscataway : IEEE, cop. 2018. — (IEEE International Conference on Cloud Computing ; ISSN 2159-6190). — e-ISBN: 978-1-5386-7235-8. — S. 460–467. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 467, Abstr.

Autorzy (5)

Słowa kluczowe

FaaSserverless computingcloud functionstask schedulingscientific workflow

Dane bibliometryczne

ID BaDAP116614
Data dodania do BaDAP2018-09-26
Tekst źródłowyURL
DOI10.1109/CLOUD.2018.00065
Rok publikacji2018
Typ publikacjimateriały konferencyjne (aut.)
Otwarty dostęptak
WydawcaInstitute of Electrical and Electronics Engineers (IEEE)
KonferencjaIEEE International Conference on Cloud Computing 2018
Czasopismo/seriaIEEE International Conference on Cloud Computing

Abstract

Serverless computing, also known as Function-as-a-Service (FaaS) or Cloud Functions, is a new method of running distributed applications by executing functions on the infrastructure of cloud providers. Although it frees the developers from managing servers, there are still decisions to be made regarding selection of function configurations based on the desired performance and cost. The billing model of this approach considers time of execution, measured in 100ms units, as well as the size of the memory allocated per function. In this paper, we look into the problem of scheduling scientific workflows, which are applications consisting of multiple tasks connected into a dependency graph. We discuss challenges related to workflow scheduling and propose the Serverless Deadline-Budget Workflow Scheduling (SDBWS) algorithm adapted to serverless platforms. We present preliminary experiments with a small-scale Montage workflow run on the AWS Lambda infrastructure.

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