Abstract
Computing resources in data centers are usually managed by a Resource and Job Management System whose main objective is to complete submitted jobs as soon as possible while maximizing resource usage and ensuring fairness among users. However, some users might not be as hurried as the job scheduler but only interested in their jobs to complete before a given deadline. In this paper, we derive from this initial hypothesis a low-complexity scheduling algorithm, called Deadline-Based Backfilling (DBF), that distinguishes regular jobs that have to complete as early as possible from deadline-driven jobs that come with a deadline before when they have to finish. We also investigate a scenario in which deadline-driven jobs are submitted and evaluate the impact of the proposed algorithm on classical performance metrics with regard to state-of-the-art scheduling algorithms. Experiments conducted on four different workloads show that the proposed algorithm significantly reduces the average wait time and average stretch when compared to Conservative Backfilling.
Original language | English |
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Title of host publication | Job Scheduling Strategies for Parallel Processing - 21st International Workshop, JSSPP 2017,Revised Selected Papers |
Editors | Narayan Desai, Dalibor Klusacek, Walfredo Cirne |
Publisher | Springer Verlag |
Pages | 62-82 |
Number of pages | 21 |
ISBN (Print) | 9783319773971 |
DOIs | |
State | Published - 2018 |
Externally published | Yes |
Event | 21st International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2017 - Orlando, United States Duration: Jun 2 2017 → Jun 2 2017 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 10773 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 21st International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2017 |
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Country/Territory | United States |
City | Orlando |
Period | 06/2/17 → 06/2/17 |
Funding
Work partially supported by the MOEBUS ANR project (13-ANR-INFR-01).