A Taxonomy of Schedulers – Operating Systems, Clusters and Big Data Frameworks

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CSTB0BTI6

A Taxonomy of Schedulers – Operating Systems, Clusters and Big Data Frameworks

Leszek Sliwko
Leszek Sliwko Axis Applications Limited
DOI

Abstract

This review analyzes deployed and actively used workload schedulers’ solutions and presents a taxonomy in which those systems are divided into several hierarchical groups based on their architecture and design. While other taxonomies do exist, this review has focused on the key design factors that affect the throughput and scalability of a given solution, as well as the incremental improvements which bettered such an architecture. This review gives special attention to Google’s Borg, which is one of the most advanced and published systems of this kind.

A Taxonomy of Schedulers – Operating Systems, Clusters and Big Data Frameworks

This review analyzes deployed and actively used workload schedulers’ solutions and presents a taxonomy in which those systems are divided into several hierarchical groups based on their architecture and design. While other taxonomies do exist, this review has focused on the key design factors that affect the throughput and scalability of a given solution, as well as the incremental improvements which bettered such an architecture. This review gives special attention to Google’s Borg, which is one of the most advanced and published systems of this kind.

Leszek Sliwko
Leszek Sliwko Axis Applications Limited

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Leszek Sliwko. 2019. “. Global Journal of Computer Science and Technology – B: Cloud & Distributed GJCST-B Volume 19 (GJCST Volume 19 Issue B1): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Issue Cover
GJCST Volume 19 Issue B1
Pg. 25- 40
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GJCST-B Classification: I.2.8
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A Taxonomy of Schedulers – Operating Systems, Clusters and Big Data Frameworks

Leszek Sliwko
Leszek Sliwko Axis Applications Limited

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