Szczegóły publikacji
Opis bibliograficzny
Adaptive multi-level workflow scheduling with uncertain task estimates / Tomasz Dziok, Kamil FIGIELA, Maciej MALAWSKI // W: Parallel Processing and Applied Mathematics : 11th international conference, PPAM 2015 : Krakow, Poland, September 6–9, 2015 : revised selected papers, Pt. 2 / eds. Roman Wyrzykowski, [et al.]. — Swizerland : Springer International Publishing, cop. 2016. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; 9574). — ISBN: 978-3-319-32151-6; e-ISBN: 978-3-319-32152-3. — S. 90–100. — Bibliogr. s. 99–100, Abstr.
Autorzy (3)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 97579 |
|---|---|
| Data dodania do BaDAP | 2016-05-13 |
| DOI | 10.1007/978-3-319-32152-3_9 |
| Rok publikacji | 2016 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp | |
| Konferencja | International Conference on Parallel Processing and Applied Mathematics 2015 |
| Czasopisma/serie | Lecture Notes in Computer Science, Theoretical Computer Science and General Issues |
Abstract
Scheduling of scientific workflows in IaaS clouds with pay- per-use pricing model and multiple types of virtual machines is an important challenge. Most static scheduling algorithms assume that the estimates of task runtimes are known in advance, while in reality the actual runtime may vary. To address this problem, we propose an adap- tive scheduling algorithm for deadline constrained workflows consisting of multiple levels. The algorithm produces a global approximate plan for the whole workflow in a first phase, and a local detailed schedule for the current level of the workflow. By applying this procedure iteratively after each level completes, the algorithm is able to adjust to the run- time variation. For each phase we propose optimization models that are solved using Mixed Integer Programming (MIP) method. The prelimi- nary simulation results using data from Amazon infrastructure, and both synthetic and Montage workflows, show that the adaptive approach has advantages over a static one.