Publication detail

Heterogeneity-Aware Scheduler for Stream Processing Frameworks

RYCHLÝ, M. ŠKODA, P. SMRŽ, P.

Original Title

Heterogeneity-Aware Scheduler for Stream Processing Frameworks

Type

journal article - other

Language

English

Original Abstract

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.

Keywords

scheduling; resource awareness; benchmarking; stream processing; Apache Storm; heterogeneous clusters; heterogeneity awareness; resource allocation

Authors

RYCHLÝ, M.; ŠKODA, P.; SMRŽ, P.

RIV year

2015

Released

1. 5. 2015

ISBN

2053-1397

Periodical

International Journal of Big Data Intelligence

Year of study

2

Number

2

State

United Kingdom of Great Britain and Northern Ireland

Pages from

70

Pages to

80

Pages count

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"
}