Přístupnostní navigace
E-přihláška
Vyhledávání Vyhledat Zavřít
Detail publikace
RYCHLÝ, M. ŠKODA, P. SMRŽ, P.
Originální název
Heterogeneity-Aware Scheduler for Stream Processing Frameworks
Typ
článek v časopise - ostatní, Jost
Jazyk
angličtina
Originální abstrakt
This article discusses problems and decisions related to scheduling of stream processing applications in heterogeneous clusters. An overview of the current state of the art of the stream processing on heterogeneous clusters with a focus on resource allocation and scheduling is presented first. Then, common scheduling approaches of various stream processing frameworks are discussed and their limited applicability in the heterogeneous environment is demonstrated on a simple stream application. Finally, the article presents a novel heterogeneity-aware scheduler for the stream processing frameworks based on design-time knowledge as well as benchmarking techniques. It is shown that the scheduler overcomes alternatives in resource-aware deployment over cluster nodes and thus it leads to a better utilisation of the clusters.
Klíčová slova
scheduling; resource awareness; benchmarking; stream processing; Apache Storm; heterogeneous clusters; heterogeneity awareness; resource allocation
Autoři
RYCHLÝ, M.; ŠKODA, P.; SMRŽ, P.
Rok RIV
2015
Vydáno
1. 5. 2015
ISSN
2053-1397
Periodikum
International Journal of Big Data Intelligence
Ročník
2
Číslo
Stát
Spojené království Velké Británie a Severního Irska
Strany od
70
Strany do
80
Strany počet
11
URL
http://www.inderscience.com/info/inarticle.php?artid=69090
BibTex
@article{BUT119792, author="Marek {Rychlý} and Petr {Škoda} and Pavel {Smrž}", title="Heterogeneity-Aware Scheduler for Stream Processing Frameworks", journal="International Journal of Big Data Intelligence", year="2015", volume="2", number="2", pages="70--80", doi="10.1504/IJBDI.2015.069090", issn="2053-1397", url="http://www.inderscience.com/info/inarticle.php?artid=69090" }
Dokumenty
IJBDI020201_RYCHLY.pdf