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Autonomic resource contention‐aware scheduling
Author(s) -
Sheikhalishahi Mehdi,
Grandinetti Lucio,
Wallace Richard M.,
VazquezPoletti Jose Luis
Publication year - 2015
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.2223
Subject(s) - computer science , distributed computing , scheduling (production processes) , novelty , resource consumption , resource management system , energy consumption , autonomic computing , resource allocation , cloud computing , computer network , operating system , mathematical optimization , ecology , philosophy , mathematics , theology , biology
SUMMARY The 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.