Autonomic resource contention-aware scheduling

SUMMARYThe complexity of computing systems introduces a few issues and challenges such as poor performance and high energy consumption. In this paper, we first define and model resource contention metric for high performance computing workloads as a performance metric in scheduling algorithms and sy...

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Bibliographic Details
Published in:Software, practice & experience practice & experience, 2015-02, Vol.45 (2), p.161-175
Main Authors: Sheikhalishahi, Mehdi, Grandinetti, Lucio, Wallace, Richard M., Vazquez-Poletti, Jose Luis
Format: Article
Language:English
Subjects:
autonomic scheduling
cloud computing
Computation
Computer programs
high performance computing
Performance measurement
resource contention
Resource scheduling
Resources management
Scheduling
Stacks
Workload
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Summary:SUMMARYThe complexity of computing systems introduces a few issues and challenges such as poor performance and high energy consumption. In this paper, we first define and model resource contention metric for high performance computing workloads as a performance metric in scheduling algorithms and systems at the highest level of resource management stack to address the main issues in computing systems. Second, we propose a novel autonomic resource contention‐aware scheduling approach architected on various layers of the resource management stack. We establish the relationship between distributed resource management layers in order to optimize resource contention metric. The simulation results confirm the novelty of our approach.Copyright © 2013 John Wiley & Sons, Ltd.
ISSN:0038-0644
1097-024X
DOI:10.1002/spe.2223